{
 "alpha_family": {
  "value": 0.05,
  "unit": "probability",
  "estimand": {
   "population": "analyst judgment",
   "filter": "Phase 3 plan",
   "statistic": "family-wise error rate over the confirmatory predictions, controlled by the Holm procedure"
  },
  "source": "q02_judgments.py",
  "kind": "judgment"
 },
 "auc_chance": {
  "value": 0.5,
  "unit": "AUC",
  "estimand": {
   "population": "definition",
   "filter": "none",
   "statistic": "AUC of a score unrelated to the label"
  },
  "source": "q02_judgments.py",
  "kind": "value"
 },
 "band_hi_v7_hz": {
  "value": 5000.0,
  "unit": "Hz",
  "estimand": {
   "population": "analyst judgment",
   "filter": "Phase 3 plan",
   "statistic": "upper edge of the searched band in variant V7"
  },
  "source": "q02_judgments.py",
  "kind": "judgment"
 },
 "comb_bins_v6a": {
  "value": 1,
  "unit": "bins",
  "estimand": {
   "population": "analyst judgment",
   "filter": "Phase 3 plan",
   "statistic": "narrower comb of variant V6a: bins treated as harmonic on each side of a spindle harmonic"
  },
  "source": "q02_judgments.py",
  "kind": "judgment"
 },
 "comb_bins_v6b": {
  "value": 3,
  "unit": "bins",
  "estimand": {
   "population": "analyst judgment",
   "filter": "Phase 3 plan",
   "statistic": "wider comb of variant V6b: bins treated as harmonic on each side of a spindle harmonic"
  },
  "source": "q02_judgments.py",
  "kind": "judgment"
 },
 "comb_check_acc0_n": {
  "value": 1386,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1 pooled (labels not used), spindle at least the comb floor",
   "statistic": "paths with a acc0 spectrum"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "comb_check_acc0_share_displaced": {
  "value": 0.022366522366522368,
  "unit": "fraction",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1 pooled (labels not used), spindle at least the comb floor",
   "statistic": "share of paths whose dominant acc0 line lies above comb_check_order_floor and more than d5_comb_bins but at most comb_check_window_bins from the nearest harmonic"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "comb_check_order_floor": {
  "value": 10,
  "unit": "harmonic order",
  "estimand": {
   "population": "analyst judgment",
   "filter": "Phase 3 plan",
   "statistic": "harmonic order above which a spindle speed error of a fraction of a percent can move a harmonic line by more than a bin"
  },
  "source": "q03_population.py",
  "kind": "judgment"
 },
 "comb_check_s2_n": {
  "value": 1386,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1 pooled (labels not used), spindle at least the comb floor",
   "statistic": "paths with a s2 spectrum"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "comb_check_s2_share_displaced": {
  "value": 0.012987012987012988,
  "unit": "fraction",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1 pooled (labels not used), spindle at least the comb floor",
   "statistic": "share of paths whose dominant s2 line lies above comb_check_order_floor and more than d5_comb_bins but at most comb_check_window_bins from the nearest harmonic"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "comb_check_window_bins": {
  "value": 6,
  "unit": "bins",
  "estimand": {
   "population": "analyst judgment",
   "filter": "Phase 3 plan",
   "statistic": "outer edge of the window just outside the comb in which a displaced harmonic line would be read as off-harmonic"
  },
  "source": "q03_population.py",
  "kind": "judgment"
 },
 "comb_offfrac_acc0_at_d5_min": {
  "value": 0.375,
  "unit": "fraction",
  "estimand": {
   "population": "definition",
   "filter": "acc0 bin width, comb of d5_comb_bins bins, spindle at d5_min_rpm",
   "statistic": "share of the searched band outside the harmonic comb"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "comb_offfrac_acc0_at_speed_class_edge": {
  "value": 0.7916666666666666,
  "unit": "fraction",
  "estimand": {
   "population": "definition",
   "filter": "acc0 bin width, comb of d5_comb_bins bins, spindle at speed_class_edge_rpm",
   "statistic": "share of the searched band outside the harmonic comb"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "comb_offfrac_s2_at_d5_min": {
  "value": 0.4140625,
  "unit": "fraction",
  "estimand": {
   "population": "definition",
   "filter": "s2 bin width, comb of d5_comb_bins bins, spindle at d5_min_rpm",
   "statistic": "share of the searched band outside the harmonic comb"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "comb_offfrac_s2_at_speed_class_edge": {
  "value": 0.8046875,
  "unit": "fraction",
  "estimand": {
   "population": "definition",
   "filter": "s2 bin width, comb of d5_comb_bins bins, spindle at speed_class_edge_rpm",
   "statistic": "share of the searched band outside the harmonic comb"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "conf_plan": {
  "value": 0.6,
  "unit": "probability",
  "estimand": {
   "population": "analyst judgment",
   "filter": "Phase 3 plan",
   "statistic": "confidence that executing this plan yields a manuscript that passes the IJAMT desk"
  },
  "source": "q02_judgments.py",
  "kind": "judgment"
 },
 "conf_plan_target": {
  "value": 0.7,
  "unit": "probability",
  "estimand": {
   "population": "analyst judgment",
   "filter": "Phase 3 plan",
   "statistic": "confidence level below which the plan must state what evidence would raise it"
  },
  "source": "q02_judgments.py",
  "kind": "judgment"
 },
 "env_matplotlib": {
  "value": "3.10.9",
  "unit": "text",
  "estimand": {
   "population": "this workspace",
   "filter": "installed software",
   "statistic": "Matplotlib version"
  },
  "source": "q00_env.py",
  "kind": "text"
 },
 "env_numpy": {
  "value": "2.4.4",
  "unit": "text",
  "estimand": {
   "population": "this workspace",
   "filter": "installed software",
   "statistic": "NumPy version"
  },
  "source": "q00_env.py",
  "kind": "text"
 },
 "env_pandas": {
  "value": "3.0.2",
  "unit": "text",
  "estimand": {
   "population": "this workspace",
   "filter": "installed software",
   "statistic": "pandas version"
  },
  "source": "q00_env.py",
  "kind": "text"
 },
 "env_pdflatex": {
  "value": "present",
  "unit": "text",
  "estimand": {
   "population": "this workspace",
   "filter": "installed software",
   "statistic": "pdflatex on the path"
  },
  "source": "q00_env.py",
  "kind": "text"
 },
 "env_python": {
  "value": "3.11.15",
  "unit": "text",
  "estimand": {
   "population": "this workspace",
   "filter": "installed software",
   "statistic": "Python version"
  },
  "source": "q00_env.py",
  "kind": "text"
 },
 "env_sklearn": {
  "value": "1.8.0",
  "unit": "text",
  "estimand": {
   "population": "this workspace",
   "filter": "installed software",
   "statistic": "scikit-learn version"
  },
  "source": "q00_env.py",
  "kind": "text"
 },
 "env_texlive": {
  "value": "TeX Live 2023",
  "unit": "text",
  "estimand": {
   "population": "this workspace",
   "filter": "installed software",
   "statistic": "TeX distribution as reported by tex --version"
  },
  "source": "q00_env.py",
  "kind": "text"
 },
 "err_mult_highrate": {
  "value": 7.338959095443979,
  "unit": "ratio",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate",
   "statistic": "factor by which a fall of thr_auc_drop from s1_auc_imi_vm20i_highrate_run (the Phase 2 screen's median per-repeat AUC) would multiply the share of misordered label 1 and label 0 pairs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "err_mult_mtc": {
  "value": 2.8375831485587573,
  "unit": "ratio",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc",
   "statistic": "factor by which a fall of thr_auc_drop from s1_auc_imi_vm20i_mtc_run (the Phase 2 screen's median per-repeat AUC) would multiply the share of misordered label 1 and label 0 pairs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "fig1_height_mm": {
  "value": 60.0,
  "unit": "mm",
  "estimand": {
   "population": "analyst judgment",
   "filter": "Phase 3 plan",
   "statistic": "height of Fig. 1 at final size"
  },
  "source": "q02_judgments.py",
  "kind": "judgment"
 },
 "fig2_height_mm": {
  "value": 60.0,
  "unit": "mm",
  "estimand": {
   "population": "analyst judgment",
   "filter": "Phase 3 plan",
   "statistic": "height of Fig. 2 at final size"
  },
  "source": "q02_judgments.py",
  "kind": "judgment"
 },
 "fig3_height_mm": {
  "value": 100.0,
  "unit": "mm",
  "estimand": {
   "population": "analyst judgment",
   "filter": "Phase 3 plan",
   "statistic": "height of Fig. 3 at final size"
  },
  "source": "q02_judgments.py",
  "kind": "judgment"
 },
 "fig4_height_mm": {
  "value": 70.0,
  "unit": "mm",
  "estimand": {
   "population": "analyst judgment",
   "filter": "Phase 3 plan",
   "statistic": "height of Fig. 4 at final size"
  },
  "source": "q02_judgments.py",
  "kind": "judgment"
 },
 "fig5_height_mm": {
  "value": 70.0,
  "unit": "mm",
  "estimand": {
   "population": "analyst judgment",
   "filter": "Phase 3 plan",
   "statistic": "height of Fig. 5 at final size"
  },
  "source": "q02_judgments.py",
  "kind": "judgment"
 },
 "fig_font_pt": {
  "value": 8,
  "unit": "pt",
  "estimand": {
   "population": "analyst judgment",
   "filter": "Phase 3 plan",
   "statistic": "lettering size of every figure at final size"
  },
  "source": "q02_judgments.py",
  "kind": "judgment"
 },
 "fig_line_pt": {
  "value": 0.5,
  "unit": "pt",
  "estimand": {
   "population": "analyst judgment",
   "filter": "Phase 3 plan",
   "statistic": "thinnest line in any figure at final size"
  },
  "source": "q02_judgments.py",
  "kind": "judgment"
 },
 "freeze_sha256_plan": {
  "value": "418905f9f0258c8e86d1e5ed4777d2b7e4e15a242beaaa97672039e7dcc91c99",
  "unit": "text",
  "estimand": {
   "population": "Phase 3 pre-registration files",
   "filter": "inputs/plan.json",
   "statistic": "sha256 of the file at the freeze"
  },
  "source": "q06_freeze.py",
  "kind": "text"
 },
 "freeze_sha256_q_common": {
  "value": "2c56868ff0b82f745a717642b43f739aa22bbde7056993bb3783b2cde445fe5b",
  "unit": "text",
  "estimand": {
   "population": "Phase 3 pre-registration files",
   "filter": "code/q_common.py",
   "statistic": "sha256 of the file at the freeze"
  },
  "source": "q06_freeze.py",
  "kind": "text"
 },
 "freeze_sha256_q_confirm": {
  "value": "4fbf8521d3fc67f0ec981de973801f3a415412587fc5d1f5e6000085a43c3da6",
  "unit": "text",
  "estimand": {
   "population": "Phase 3 pre-registration files",
   "filter": "code/q_confirm.py",
   "statistic": "sha256 of the file at the freeze"
  },
  "source": "q06_freeze.py",
  "kind": "text"
 },
 "freeze_sha256_q_rules": {
  "value": "e38d55b2691e1776a9c4818902ab2ad78e13e3054f5c0d6353cb11b76f141efd",
  "unit": "text",
  "estimand": {
   "population": "Phase 3 pre-registration files",
   "filter": "code/q_rules.py",
   "statistic": "sha256 of the file at the freeze"
  },
  "source": "q06_freeze.py",
  "kind": "text"
 },
 "freeze_time": {
  "value": "2026-09-23T00:53:06Z",
  "unit": "text",
  "estimand": {
   "population": "Phase 3 pre-registration files",
   "filter": "q06_freeze.py",
   "statistic": "time the hashes were taken (UTC)"
  },
  "source": "q06_freeze.py",
  "kind": "text"
 },
 "freq_match_tol_hz": {
  "value": 12.5,
  "unit": "Hz",
  "estimand": {
   "population": "analyst judgment",
   "filter": "Phase 3 plan",
   "statistic": "largest difference between the Acc0 and Sound2 off-harmonic line frequencies that counts as the same line in E9 (two bins of the Acc0 spectrum)"
  },
  "source": "q02_judgments.py",
  "kind": "judgment"
 },
 "kappa_independent": {
  "value": 0.0,
  "unit": "kappa",
  "estimand": {
   "population": "definition",
   "filter": "none",
   "statistic": "kappa of two indicators that are independent"
  },
  "source": "q02_judgments.py",
  "kind": "value"
 },
 "kappa_max_l1_pooled": {
  "value": 0.8207171314741036,
  "unit": "kappa",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, Acc0 and Sound2 spectra",
   "statistic": "largest kappa the Phase 2 per-sensor shares in label 1 allow, speed classes pooled"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "keywords_planned": {
  "value": 5,
  "unit": "keywords",
  "estimand": {
   "population": "analyst judgment",
   "filter": "Phase 3 plan",
   "statistic": "keywords planned for the title page"
  },
  "source": "q02_judgments.py",
  "kind": "judgment"
 },
 "lr_c": {
  "value": 1.0,
  "unit": "inverse penalty",
  "estimand": {
   "population": "analyst judgment",
   "filter": "Phase 3 plan",
   "statistic": "inverse regularisation strength of the logistic model (the scikit-learn default used by the Phase 2 screen)"
  },
  "source": "q02_judgments.py",
  "kind": "judgment"
 },
 "max_nonfinite_share": {
  "value": 0.01,
  "unit": "fraction",
  "estimand": {
   "population": "analyst judgment",
   "filter": "Phase 3 plan",
   "statistic": "largest share of bootstrap draws that may be undefined before a prediction is NOT_TESTED"
  },
  "source": "q02_judgments.py",
  "kind": "judgment"
 },
 "min_pos_testable": {
  "value": 30,
  "unit": "paths",
  "estimand": {
   "population": "analyst judgment",
   "filter": "Phase 3 plan",
   "statistic": "fewest label 1 paths in any training set, comparison group or family for a statistic to be computed"
  },
  "source": "q02_judgments.py",
  "kind": "judgment"
 },
 "p_fail_indicator": {
  "value": 0.25,
  "unit": "probability",
  "estimand": {
   "population": "analyst judgment",
   "filter": "Phase 3 plan",
   "statistic": "probability that the spectral indicator is judged unvalidated, so the chatter part of the paper cannot stand"
  },
  "source": "q02_judgments.py",
  "kind": "judgment"
 },
 "p_fail_null": {
  "value": 0.2,
  "unit": "probability",
  "estimand": {
   "population": "analyst judgment",
   "filter": "Phase 3 plan",
   "statistic": "probability that no prediction is confirmed and robust, leaving only findings already seen in Phase 2"
  },
  "source": "q02_judgments.py",
  "kind": "judgment"
 },
 "p_fail_tool": {
  "value": 0.3,
  "unit": "probability",
  "estimand": {
   "population": "analyst judgment",
   "filter": "Phase 3 plan",
   "statistic": "probability that the tool analysis (H1, H2) is judged a property of this one design and cannot support a general recommendation"
  },
  "source": "q02_judgments.py",
  "kind": "judgment"
 },
 "pop_agree_excluded_slow": {
  "value": 112,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1",
   "statistic": "paths below the lowest spindle speed of the harmonic comb (no spectral indicator)"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_agree_excluded_slow_l1": {
  "value": 0,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1",
   "statistic": "label 1 paths below the lowest spindle speed of the harmonic comb"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_agree_no_early_n": {
  "value": 1364,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, spindle at least the comb floor, Acc0 and Sound2 spectra, variant no_early",
   "statistic": "paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_agree_no_early_n_l1": {
  "value": 315,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, agreement population, variant no_early",
   "statistic": "label 1 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_agree_no_early_runs": {
  "value": 26,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, agreement population, variant no_early",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_agree_no_early_runs_l1": {
  "value": 12,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, agreement population, variant no_early",
   "statistic": "runs holding label 1"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_agree_no_twins_n": {
  "value": 1355,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, spindle at least the comb floor, Acc0 and Sound2 spectra, variant no_twins",
   "statistic": "paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_agree_no_twins_n_l1": {
  "value": 294,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, agreement population, variant no_twins",
   "statistic": "label 1 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_agree_no_twins_runs": {
  "value": 31,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, agreement population, variant no_twins",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_agree_no_twins_runs_l1": {
  "value": 17,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, agreement population, variant no_twins",
   "statistic": "runs holding label 1"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_agree_primary_n": {
  "value": 1386,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, spindle at least the comb floor, Acc0 and Sound2 spectra, variant primary",
   "statistic": "paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_agree_primary_n_l1": {
  "value": 325,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, agreement population, variant primary",
   "statistic": "label 1 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_agree_primary_runs": {
  "value": 33,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, agreement population, variant primary",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_agree_primary_runs_l1": {
  "value": 19,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, agreement population, variant primary",
   "statistic": "runs holding label 1"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_bytool_no_early_a_n": {
  "value": 247,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, Acc0 spectrum defined, family A, variant no_early",
   "statistic": "paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_bytool_no_early_a_runs": {
  "value": 8,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, Acc0 spectrum defined, family A, variant no_early",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_bytool_no_early_n": {
  "value": 315,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, Acc0 spectrum defined, variant no_early",
   "statistic": "paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_bytool_no_early_other_n": {
  "value": 68,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, Acc0 spectrum defined, family other than A, variant no_early",
   "statistic": "paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_bytool_no_early_other_runs": {
  "value": 4,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, Acc0 spectrum defined, family other than A, variant no_early",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_bytool_no_twins_a_n": {
  "value": 241,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, Acc0 spectrum defined, family A, variant no_twins",
   "statistic": "paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_bytool_no_twins_a_runs": {
  "value": 10,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, Acc0 spectrum defined, family A, variant no_twins",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_bytool_no_twins_n": {
  "value": 294,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, Acc0 spectrum defined, variant no_twins",
   "statistic": "paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_bytool_no_twins_other_n": {
  "value": 53,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, Acc0 spectrum defined, family other than A, variant no_twins",
   "statistic": "paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_bytool_no_twins_other_runs": {
  "value": 7,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, Acc0 spectrum defined, family other than A, variant no_twins",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_bytool_primary_a_n": {
  "value": 253,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, Acc0 spectrum defined, family A, variant primary",
   "statistic": "paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_bytool_primary_a_runs": {
  "value": 11,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, Acc0 spectrum defined, family A, variant primary",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_bytool_primary_n": {
  "value": 325,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, Acc0 spectrum defined, variant primary",
   "statistic": "paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_bytool_primary_other_n": {
  "value": 72,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, Acc0 spectrum defined, family other than A, variant primary",
   "statistic": "paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_bytool_primary_other_runs": {
  "value": 8,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, Acc0 spectrum defined, family other than A, variant primary",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_early_runs_lab": {
  "value": 9,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "laboratory runs",
   "statistic": "runs whose summary remark records an early stop"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h3_no_early_hi_families": {
  "value": 2,
  "unit": "families",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, Acc0 and Sound2 spectra, spindle speed at or above speed_class_edge_rpm, variant no_early",
   "statistic": "tool families"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h3_no_early_hi_n": {
  "value": 256,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, Acc0 and Sound2 spectra, spindle speed at or above speed_class_edge_rpm, variant no_early",
   "statistic": "paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h3_no_early_hi_runs": {
  "value": 11,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, Acc0 and Sound2 spectra, spindle speed at or above speed_class_edge_rpm, variant no_early",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h3_no_early_lo_families": {
  "value": 2,
  "unit": "families",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, Acc0 and Sound2 spectra, spindle speed below speed_class_edge_rpm, variant no_early",
   "statistic": "tool families"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h3_no_early_lo_n": {
  "value": 59,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, Acc0 and Sound2 spectra, spindle speed below speed_class_edge_rpm, variant no_early",
   "statistic": "paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h3_no_early_lo_runs": {
  "value": 7,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, Acc0 and Sound2 spectra, spindle speed below speed_class_edge_rpm, variant no_early",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h3_no_twins_hi_families": {
  "value": 3,
  "unit": "families",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, Acc0 and Sound2 spectra, spindle speed at or above speed_class_edge_rpm, variant no_twins",
   "statistic": "tool families"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h3_no_twins_hi_n": {
  "value": 237,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, Acc0 and Sound2 spectra, spindle speed at or above speed_class_edge_rpm, variant no_twins",
   "statistic": "paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h3_no_twins_hi_runs": {
  "value": 10,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, Acc0 and Sound2 spectra, spindle speed at or above speed_class_edge_rpm, variant no_twins",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h3_no_twins_lo_families": {
  "value": 3,
  "unit": "families",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, Acc0 and Sound2 spectra, spindle speed below speed_class_edge_rpm, variant no_twins",
   "statistic": "tool families"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h3_no_twins_lo_n": {
  "value": 57,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, Acc0 and Sound2 spectra, spindle speed below speed_class_edge_rpm, variant no_twins",
   "statistic": "paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h3_no_twins_lo_runs": {
  "value": 12,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, Acc0 and Sound2 spectra, spindle speed below speed_class_edge_rpm, variant no_twins",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h3_primary_hi_families": {
  "value": 3,
  "unit": "families",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, Acc0 and Sound2 spectra, spindle speed at or above speed_class_edge_rpm, variant primary",
   "statistic": "tool families"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h3_primary_hi_n": {
  "value": 257,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, Acc0 and Sound2 spectra, spindle speed at or above speed_class_edge_rpm, variant primary",
   "statistic": "paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h3_primary_hi_runs": {
  "value": 12,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, Acc0 and Sound2 spectra, spindle speed at or above speed_class_edge_rpm, variant primary",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h3_primary_lo_families": {
  "value": 3,
  "unit": "families",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, Acc0 and Sound2 spectra, spindle speed below speed_class_edge_rpm, variant primary",
   "statistic": "tool families"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h3_primary_lo_n": {
  "value": 68,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, Acc0 and Sound2 spectra, spindle speed below speed_class_edge_rpm, variant primary",
   "statistic": "paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h3_primary_lo_runs": {
  "value": 13,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, Acc0 and Sound2 spectra, spindle speed below speed_class_edge_rpm, variant primary",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_highrate_no_early_families": {
  "value": 6,
  "unit": "families",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate features present, variant no_early",
   "statistic": "tool families (folds of the family scheme)"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_highrate_no_early_min_train_l0_family": {
  "value": 734,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate features present, variant no_early",
   "statistic": "fewest label 0 paths in a tool-family-held-out training set"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_highrate_no_early_min_train_l0_run": {
  "value": 821,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate features present, variant no_early",
   "statistic": "fewest label 0 paths in a run-held-out training fold over all repeats"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_highrate_no_early_min_train_l1_family": {
  "value": 68,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate features present, variant no_early",
   "statistic": "fewest label 1 paths in a tool-family-held-out training set"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_highrate_no_early_min_train_l1_run": {
  "value": 169,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate features present, variant no_early",
   "statistic": "fewest label 1 paths in a run-held-out training fold over all repeats"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_highrate_no_early_n": {
  "value": 1476,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate features present, variant no_early",
   "statistic": "paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_highrate_no_early_n_l1": {
  "value": 315,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate features present, variant no_early",
   "statistic": "label 1 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_highrate_no_early_runs": {
  "value": 27,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate features present, variant no_early",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_highrate_no_early_runs_l1": {
  "value": 12,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate features present, variant no_early",
   "statistic": "runs holding label 1"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_highrate_no_early_train_l1_share_max_family": {
  "value": 0.27249134948096887,
  "unit": "fraction",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate features present, variant no_early",
   "statistic": "largest label 1 share among the tool-family-held-out training sets"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_highrate_no_early_train_l1_share_min_family": {
  "value": 0.06349206349206349,
  "unit": "fraction",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate features present, variant no_early",
   "statistic": "smallest label 1 share among the tool-family-held-out training sets"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_highrate_no_twins_families": {
  "value": 6,
  "unit": "families",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate features present, variant no_twins",
   "statistic": "tool families (folds of the family scheme)"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_highrate_no_twins_min_train_l0_family": {
  "value": 734,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate features present, variant no_twins",
   "statistic": "fewest label 0 paths in a tool-family-held-out training set"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_highrate_no_twins_min_train_l0_run": {
  "value": 769,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate features present, variant no_twins",
   "statistic": "fewest label 0 paths in a run-held-out training fold over all repeats"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_highrate_no_twins_min_train_l1_family": {
  "value": 53,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate features present, variant no_twins",
   "statistic": "fewest label 1 paths in a tool-family-held-out training set"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_highrate_no_twins_min_train_l1_run": {
  "value": 128,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate features present, variant no_twins",
   "statistic": "fewest label 1 paths in a run-held-out training fold over all repeats"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_highrate_no_twins_n": {
  "value": 1467,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate features present, variant no_twins",
   "statistic": "paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_highrate_no_twins_n_l1": {
  "value": 294,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate features present, variant no_twins",
   "statistic": "label 1 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_highrate_no_twins_runs": {
  "value": 32,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate features present, variant no_twins",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_highrate_no_twins_runs_l1": {
  "value": 17,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate features present, variant no_twins",
   "statistic": "runs holding label 1"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_highrate_no_twins_train_l1_share_max_family": {
  "value": 0.2556719022687609,
  "unit": "fraction",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate features present, variant no_twins",
   "statistic": "largest label 1 share among the tool-family-held-out training sets"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_highrate_no_twins_train_l1_share_min_family": {
  "value": 0.04962546816479401,
  "unit": "fraction",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate features present, variant no_twins",
   "statistic": "smallest label 1 share among the tool-family-held-out training sets"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_highrate_primary_families": {
  "value": 6,
  "unit": "families",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate features present, variant primary",
   "statistic": "tool families (folds of the family scheme)"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_highrate_primary_min_train_l0_family": {
  "value": 734,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate features present, variant primary",
   "statistic": "fewest label 0 paths in a tool-family-held-out training set"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_highrate_primary_min_train_l0_run": {
  "value": 771,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate features present, variant primary",
   "statistic": "fewest label 0 paths in a run-held-out training fold over all repeats"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_highrate_primary_min_train_l1_family": {
  "value": 72,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate features present, variant primary",
   "statistic": "fewest label 1 paths in a tool-family-held-out training set"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_highrate_primary_min_train_l1_run": {
  "value": 146,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate features present, variant primary",
   "statistic": "fewest label 1 paths in a run-held-out training fold over all repeats"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_highrate_primary_n": {
  "value": 1498,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate features present, variant primary",
   "statistic": "paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_highrate_primary_n_l1": {
  "value": 325,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate features present, variant primary",
   "statistic": "label 1 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_highrate_primary_runs": {
  "value": 34,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate features present, variant primary",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_highrate_primary_runs_l1": {
  "value": 19,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate features present, variant primary",
   "statistic": "runs holding label 1"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_highrate_primary_train_l1_share_max_family": {
  "value": 0.2752761257434155,
  "unit": "fraction",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate features present, variant primary",
   "statistic": "largest label 1 share among the tool-family-held-out training sets"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_highrate_primary_train_l1_share_min_family": {
  "value": 0.06623735050597976,
  "unit": "fraction",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate features present, variant primary",
   "statistic": "smallest label 1 share among the tool-family-held-out training sets"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_mtc_no_early_families": {
  "value": 6,
  "unit": "families",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc features present, variant no_early",
   "statistic": "tool families (folds of the family scheme)"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_mtc_no_early_min_train_l0_family": {
  "value": 734,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc features present, variant no_early",
   "statistic": "fewest label 0 paths in a tool-family-held-out training set"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_mtc_no_early_min_train_l0_run": {
  "value": 821,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc features present, variant no_early",
   "statistic": "fewest label 0 paths in a run-held-out training fold over all repeats"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_mtc_no_early_min_train_l1_family": {
  "value": 68,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc features present, variant no_early",
   "statistic": "fewest label 1 paths in a tool-family-held-out training set"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_mtc_no_early_min_train_l1_run": {
  "value": 169,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc features present, variant no_early",
   "statistic": "fewest label 1 paths in a run-held-out training fold over all repeats"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_mtc_no_early_n": {
  "value": 1476,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc features present, variant no_early",
   "statistic": "paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_mtc_no_early_n_l1": {
  "value": 315,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc features present, variant no_early",
   "statistic": "label 1 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_mtc_no_early_runs": {
  "value": 27,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc features present, variant no_early",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_mtc_no_early_runs_l1": {
  "value": 12,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc features present, variant no_early",
   "statistic": "runs holding label 1"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_mtc_no_early_train_l1_share_max_family": {
  "value": 0.27249134948096887,
  "unit": "fraction",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc features present, variant no_early",
   "statistic": "largest label 1 share among the tool-family-held-out training sets"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_mtc_no_early_train_l1_share_min_family": {
  "value": 0.06349206349206349,
  "unit": "fraction",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc features present, variant no_early",
   "statistic": "smallest label 1 share among the tool-family-held-out training sets"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_mtc_no_twins_families": {
  "value": 6,
  "unit": "families",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc features present, variant no_twins",
   "statistic": "tool families (folds of the family scheme)"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_mtc_no_twins_min_train_l0_family": {
  "value": 734,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc features present, variant no_twins",
   "statistic": "fewest label 0 paths in a tool-family-held-out training set"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_mtc_no_twins_min_train_l0_run": {
  "value": 769,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc features present, variant no_twins",
   "statistic": "fewest label 0 paths in a run-held-out training fold over all repeats"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_mtc_no_twins_min_train_l1_family": {
  "value": 53,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc features present, variant no_twins",
   "statistic": "fewest label 1 paths in a tool-family-held-out training set"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_mtc_no_twins_min_train_l1_run": {
  "value": 128,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc features present, variant no_twins",
   "statistic": "fewest label 1 paths in a run-held-out training fold over all repeats"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_mtc_no_twins_n": {
  "value": 1467,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc features present, variant no_twins",
   "statistic": "paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_mtc_no_twins_n_l1": {
  "value": 294,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc features present, variant no_twins",
   "statistic": "label 1 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_mtc_no_twins_runs": {
  "value": 32,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc features present, variant no_twins",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_mtc_no_twins_runs_l1": {
  "value": 17,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc features present, variant no_twins",
   "statistic": "runs holding label 1"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_mtc_no_twins_train_l1_share_max_family": {
  "value": 0.2556719022687609,
  "unit": "fraction",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc features present, variant no_twins",
   "statistic": "largest label 1 share among the tool-family-held-out training sets"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_mtc_no_twins_train_l1_share_min_family": {
  "value": 0.04962546816479401,
  "unit": "fraction",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc features present, variant no_twins",
   "statistic": "smallest label 1 share among the tool-family-held-out training sets"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_mtc_primary_families": {
  "value": 6,
  "unit": "families",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc features present, variant primary",
   "statistic": "tool families (folds of the family scheme)"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_mtc_primary_min_train_l0_family": {
  "value": 734,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc features present, variant primary",
   "statistic": "fewest label 0 paths in a tool-family-held-out training set"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_mtc_primary_min_train_l0_run": {
  "value": 771,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc features present, variant primary",
   "statistic": "fewest label 0 paths in a run-held-out training fold over all repeats"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_mtc_primary_min_train_l1_family": {
  "value": 72,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc features present, variant primary",
   "statistic": "fewest label 1 paths in a tool-family-held-out training set"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_mtc_primary_min_train_l1_run": {
  "value": 146,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc features present, variant primary",
   "statistic": "fewest label 1 paths in a run-held-out training fold over all repeats"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_mtc_primary_n": {
  "value": 1498,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc features present, variant primary",
   "statistic": "paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_mtc_primary_n_l1": {
  "value": 325,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc features present, variant primary",
   "statistic": "label 1 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_mtc_primary_runs": {
  "value": 34,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc features present, variant primary",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_mtc_primary_runs_l1": {
  "value": 19,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc features present, variant primary",
   "statistic": "runs holding label 1"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_mtc_primary_train_l1_share_max_family": {
  "value": 0.2752761257434155,
  "unit": "fraction",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc features present, variant primary",
   "statistic": "largest label 1 share among the tool-family-held-out training sets"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_h_mtc_primary_train_l1_share_min_family": {
  "value": 0.06623735050597976,
  "unit": "fraction",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc features present, variant primary",
   "statistic": "smallest label 1 share among the tool-family-held-out training sets"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vm20i_a_l0": {
  "value": 158,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, family A",
   "statistic": "label 0 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vm20i_a_l1": {
  "value": 253,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, family A",
   "statistic": "label 1 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vm20i_a_runs": {
  "value": 11,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, family A",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vm20i_a_runs_l1": {
  "value": 11,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, family A",
   "statistic": "runs holding label 1"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vm20i_b_l0": {
  "value": 64,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, family B",
   "statistic": "label 0 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vm20i_b_l1": {
  "value": 0,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, family B",
   "statistic": "label 1 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vm20i_b_runs": {
  "value": 1,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, family B",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vm20i_b_runs_l1": {
  "value": 0,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, family B",
   "statistic": "runs holding label 1"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vm20i_c1_l0": {
  "value": 128,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, family C1",
   "statistic": "label 0 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vm20i_c1_l1": {
  "value": 0,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, family C1",
   "statistic": "label 1 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vm20i_c1_runs": {
  "value": 2,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, family C1",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vm20i_c1_runs_l1": {
  "value": 0,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, family C1",
   "statistic": "runs holding label 1"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vm20i_d_l0": {
  "value": 320,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, family D",
   "statistic": "label 0 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vm20i_d_l1": {
  "value": 1,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, family D",
   "statistic": "label 1 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vm20i_d_runs": {
  "value": 6,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, family D",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vm20i_d_runs_l1": {
  "value": 1,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, family D",
   "statistic": "runs holding label 1"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vm20i_e_l0": {
  "value": 439,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, family E",
   "statistic": "label 0 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vm20i_e_l1": {
  "value": 70,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, family E",
   "statistic": "label 1 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vm20i_e_runs": {
  "value": 12,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, family E",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vm20i_e_runs_l1": {
  "value": 6,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, family E",
   "statistic": "runs holding label 1"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vm20i_f1_l0": {
  "value": 64,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, family F1",
   "statistic": "label 0 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vm20i_f1_l1": {
  "value": 1,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, family F1",
   "statistic": "label 1 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vm20i_f1_runs": {
  "value": 2,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, family F1",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vm20i_f1_runs_l1": {
  "value": 1,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, family F1",
   "statistic": "runs holding label 1"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vm20i_n_families": {
  "value": 6,
  "unit": "families",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1",
   "statistic": "tool families"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vmx30ui_a_l0": {
  "value": 26,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vmx30ui, family A",
   "statistic": "label 0 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vmx30ui_a_l1": {
  "value": 114,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vmx30ui, family A",
   "statistic": "label 1 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vmx30ui_a_runs": {
  "value": 3,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vmx30ui, family A",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vmx30ui_a_runs_l1": {
  "value": 3,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vmx30ui, family A",
   "statistic": "runs holding label 1"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vmx30ui_b_l0": {
  "value": 64,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vmx30ui, family B",
   "statistic": "label 0 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vmx30ui_b_l1": {
  "value": 0,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vmx30ui, family B",
   "statistic": "label 1 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vmx30ui_b_runs": {
  "value": 1,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vmx30ui, family B",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vmx30ui_b_runs_l1": {
  "value": 0,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vmx30ui, family B",
   "statistic": "runs holding label 1"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vmx30ui_c2_l0": {
  "value": 128,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vmx30ui, family C2",
   "statistic": "label 0 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vmx30ui_c2_l1": {
  "value": 0,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vmx30ui, family C2",
   "statistic": "label 1 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vmx30ui_c2_runs": {
  "value": 2,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vmx30ui, family C2",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vmx30ui_c2_runs_l1": {
  "value": 0,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vmx30ui, family C2",
   "statistic": "runs holding label 1"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vmx30ui_d_l0": {
  "value": 140,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vmx30ui, family D",
   "statistic": "label 0 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vmx30ui_d_l1": {
  "value": 2,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vmx30ui, family D",
   "statistic": "label 1 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vmx30ui_d_runs": {
  "value": 3,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vmx30ui, family D",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vmx30ui_d_runs_l1": {
  "value": 1,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vmx30ui, family D",
   "statistic": "runs holding label 1"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vmx30ui_e_l0": {
  "value": 282,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vmx30ui, family E",
   "statistic": "label 0 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vmx30ui_e_l1": {
  "value": 17,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vmx30ui, family E",
   "statistic": "label 1 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vmx30ui_e_runs": {
  "value": 6,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vmx30ui, family E",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vmx30ui_e_runs_l1": {
  "value": 2,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vmx30ui, family E",
   "statistic": "runs holding label 1"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vmx30ui_f2_l0": {
  "value": 64,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vmx30ui, family F2",
   "statistic": "label 0 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vmx30ui_f2_l1": {
  "value": 0,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vmx30ui, family F2",
   "statistic": "label 1 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vmx30ui_f2_runs": {
  "value": 1,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vmx30ui, family F2",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vmx30ui_f2_runs_l1": {
  "value": 0,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vmx30ui, family F2",
   "statistic": "runs holding label 1"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_imi_vmx30ui_n_families": {
  "value": 6,
  "unit": "families",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vmx30ui, labels 0 and 1",
   "statistic": "tool families"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_kish_l1_runs_a": {
  "value": 5.866465035285492,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, family A",
   "statistic": "effective number of runs (Kish)"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_kish_l1_runs_e": {
  "value": 3.49002849002849,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, family E",
   "statistic": "effective number of runs (Kish)"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_kish_l1_runs_no_early": {
  "value": 8.070353802358682,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, variant no_early",
   "statistic": "effective number of runs holding label 1 (Kish: squared total over sum of squared counts)"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_kish_l1_runs_no_twins": {
  "value": 7.317643074839147,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, variant no_twins",
   "statistic": "effective number of runs holding label 1 (Kish: squared total over sum of squared counts)"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_kish_l1_runs_other": {
  "value": 3.6870554765291605,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, families other than A",
   "statistic": "effective number of runs (Kish)"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_kish_l1_runs_primary": {
  "value": 8.575545993342535,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, variant primary",
   "statistic": "effective number of runs holding label 1 (Kish: squared total over sum of squared counts)"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_l1_other_top3_share": {
  "value": 0.8888888888888888,
  "unit": "fraction",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, families other than A",
   "statistic": "share of the label 1 paths held by the three largest runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_l1_runs_other_single": {
  "value": 4,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, label 1, families other than A",
   "statistic": "runs holding a single label 1 path"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_material_aa6061_l1": {
  "value": 248,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, workpiece AA 6061",
   "statistic": "label 1 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_material_aa6061_runs": {
  "value": 11,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, workpiece AA 6061",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_material_aa6061_runs_l1": {
  "value": 9,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, workpiece AA 6061",
   "statistic": "runs holding label 1"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_material_aisi1018_l1": {
  "value": 32,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, workpiece AISI 1018",
   "statistic": "label 1 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_material_aisi1018_runs": {
  "value": 12,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, workpiece AISI 1018",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_material_aisi1018_runs_l1": {
  "value": 7,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, workpiece AISI 1018",
   "statistic": "runs holding label 1"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_material_aisi4140_l1": {
  "value": 45,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, workpiece AISI 4140",
   "statistic": "label 1 paths"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_material_aisi4140_runs": {
  "value": 11,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, workpiece AISI 4140",
   "statistic": "runs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_material_aisi4140_runs_l1": {
  "value": 3,
  "unit": "runs",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, workpiece AISI 4140",
   "statistic": "runs holding label 1"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_material_min_train_l1": {
  "value": 77,
  "unit": "paths",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1",
   "statistic": "fewest label 1 paths in a leave-material-out training set"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_material_n": {
  "value": 3,
  "unit": "materials",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1",
   "statistic": "workpiece materials"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_mtc_speed_equals_n_share": {
  "value": 0.9979973297730307,
  "unit": "fraction",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1",
   "statistic": "share of paths whose MTConnect spindle speed equals N to within one part in a billion"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_within_families_no_early": {
  "value": 1,
  "unit": "families",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, variant no_early",
   "statistic": "families with enough label 1 paths, label 0 paths and runs holding label 1 for a within-family AUC"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_within_families_no_early_list": {
  "value": "A",
  "unit": "text",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, variant no_early",
   "statistic": "those families"
  },
  "source": "q03_population.py",
  "kind": "text"
 },
 "pop_within_families_no_twins": {
  "value": 2,
  "unit": "families",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, variant no_twins",
   "statistic": "families with enough label 1 paths, label 0 paths and runs holding label 1 for a within-family AUC"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_within_families_no_twins_list": {
  "value": "A, E",
  "unit": "text",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, variant no_twins",
   "statistic": "those families"
  },
  "source": "q03_population.py",
  "kind": "text"
 },
 "pop_within_families_primary": {
  "value": 2,
  "unit": "families",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, variant primary",
   "statistic": "families with enough label 1 paths, label 0 paths and runs holding label 1 for a within-family AUC"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "pop_within_families_primary_list": {
  "value": "A, E",
  "unit": "text",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, variant primary",
   "statistic": "those families"
  },
  "source": "q03_population.py",
  "kind": "text"
 },
 "prec_auc_run_highrate": {
  "value": 0.9919858351367301,
  "unit": "AUC",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate",
   "statistic": "mean over repeats of the pooled out-of-fold AUC of each repeat, Phase 2 screen model (logistic, no class weights), run-held-out scheme; the Phase 2 screen reported the median of the same per-repeat AUCs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "prec_auc_run_highrate_se": {
  "value": 0.004491867767450596,
  "unit": "AUC",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, highrate",
   "statistic": "standard error of that AUC over a family-stratified run bootstrap, predictions held fixed"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "prec_auc_run_mtc": {
  "value": 0.9719765230506919,
  "unit": "AUC",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc",
   "statistic": "mean over repeats of the pooled out-of-fold AUC of each repeat, Phase 2 screen model (logistic, no class weights), run-held-out scheme; the Phase 2 screen reported the median of the same per-repeat AUCs"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "prec_auc_run_mtc_se": {
  "value": 0.013921168772202928,
  "unit": "AUC",
  "estimand": {
   "population": "labelled cutting paths (label.csv rows)",
   "filter": "imi_vm20i, labels 0 and 1, mtc",
   "statistic": "standard error of that AUC over a family-stratified run bootstrap, predictions held fixed"
  },
  "source": "q03_population.py",
  "kind": "value"
 },
 "prec_boot_b": {
  "value": 2000,
  "unit": "resamples",
  "estimand": {
   "population": "analyst judgment",
   "filter": "Phase 3 plan",
   "statistic": "run-level resamples used only to size the decision rules"
  },
  "source": "q03_population.py",
  "kind": "judgment"
 },
 "rel_speed_tol": {
  "value": 0.005,
  "unit": "fraction",
  "estimand": {
   "population": "analyst judgment",
   "filter": "Phase 3 plan",
   "statistic": "spindle speed error covered by the relative comb of variant V6c: each harmonic zone widens to this share of the harmonic frequency when that exceeds d5_comb_bins; no measurement of the actual speed exists in the dataset"
  },
  "source": "q02_judgments.py",
  "kind": "judgment"
 },
 "rf_min_leaf": {
  "value": 5,
  "unit": "paths",
  "estimand": {
   "population": "analyst judgment",
   "filter": "Phase 3 plan",
   "statistic": "smallest leaf of the random forest of variant V3"
  },
  "source": "q02_judgments.py",
  "kind": "judgment"
 },
 "rf_trees": {
  "value": 500,
  "unit": "trees",
  "estimand": {
   "population": "analyst judgment",
   "filter": "Phase 3 plan",
   "statistic": "trees in the random forest of variant V3"
  },
  "source": "q02_judgments.py",
  "kind": "judgment"
 },
 "seed_analysis": {
  "value": 20260922,
  "unit": "seed",
  "estimand": {
   "population": "analyst judgment",
   "filter": "Phase 3 plan",
   "statistic": "seed of every random split and resample in Phases 3 and 4 (the Phase 2 seed)"
  },
  "source": "q02_judgments.py",
  "kind": "judgment"
 },
 "speed_class_edge_rpm": {
  "value": 9000,
  "unit": "r/min",
  "estimand": {
   "population": "analyst judgment",
   "filter": "Phase 3 plan",
   "statistic": "edge between the H3 spindle-speed classes among label 1 paths; each class then holds label 1 paths of more than one tool family and more than min_pos_testable paths (checked in q03_population.py)"
  },
  "source": "q02_judgments.py",
  "kind": "judgment"
 },
 "structure_levels_planned": {
  "value": 2,
  "unit": "levels",
  "estimand": {
   "population": "analyst judgment",
   "filter": "Phase 3 plan",
   "statistic": "deepest heading level planned for the manuscript (section and subsection)"
  },
  "source": "q02_judgments.py",
  "kind": "judgment"
 },
 "thr_auc_drop": {
  "value": 0.05,
  "unit": "AUC",
  "estimand": {
   "population": "analyst judgment",
   "filter": "Phase 3 plan",
   "statistic": "smallest fall in pooled AUC from run-held-out to tool-family-held-out evaluation that counts as a practical loss (H1, H2)"
  },
  "source": "q02_judgments.py",
  "kind": "judgment"
 },
 "thr_kappa_frac": {
  "value": 0.5,
  "unit": "fraction",
  "estimand": {
   "population": "analyst judgment",
   "filter": "Phase 3 plan",
   "statistic": "position of the H3 threshold on the way from the kappa expected under independence within spindle-speed classes to the largest kappa the per-class shares allow"
  },
  "source": "q02_judgments.py",
  "kind": "judgment"
 },
 "v_abstract_max_words": {
  "value": 250,
  "unit": "words",
  "estimand": {
   "population": "external source",
   "filter": "IJAMT submission guidelines, quote q_abstract, retrieved 2026-09-22",
   "statistic": "value as printed"
  },
  "source": "q01_venue.py",
  "kind": "external"
 },
 "v_abstract_min_words": {
  "value": 150,
  "unit": "words",
  "estimand": {
   "population": "external source",
   "filter": "IJAMT submission guidelines, quote q_abstract, retrieved 2026-09-22",
   "statistic": "value as printed"
  },
  "source": "q01_venue.py",
  "kind": "external"
 },
 "v_ci_window_years": {
  "value": 3,
  "unit": "years",
  "estimand": {
   "population": "external source",
   "filter": "IJAMT submission guidelines, quote q_ci_window, retrieved 2026-09-22",
   "statistic": "value as printed"
  },
  "source": "q01_venue.py",
  "kind": "external"
 },
 "v_contrast_min": {
  "value": 4.5,
  "unit": "ratio",
  "estimand": {
   "population": "external source",
   "filter": "IJAMT submission guidelines, quote q_contrast, retrieved 2026-09-22",
   "statistic": "value as printed"
  },
  "source": "q01_venue.py",
  "kind": "external"
 },
 "v_dpi_combination": {
  "value": 600,
  "unit": "dpi",
  "estimand": {
   "population": "external source",
   "filter": "IJAMT submission guidelines, quote q_combo, retrieved 2026-09-22",
   "statistic": "value as printed"
  },
  "source": "q01_venue.py",
  "kind": "external"
 },
 "v_dpi_halftone": {
  "value": 300,
  "unit": "dpi",
  "estimand": {
   "population": "external source",
   "filter": "IJAMT submission guidelines, quote q_halftone, retrieved 2026-09-22",
   "statistic": "value as printed"
  },
  "source": "q01_venue.py",
  "kind": "external"
 },
 "v_dpi_lineart": {
  "value": 1200,
  "unit": "dpi",
  "estimand": {
   "population": "external source",
   "filter": "IJAMT submission guidelines, quote q_lineart, retrieved 2026-09-22",
   "statistic": "value as printed"
  },
  "source": "q01_venue.py",
  "kind": "external"
 },
 "v_fig_height_max_mm": {
  "value": 234.0,
  "unit": "mm",
  "estimand": {
   "population": "external source",
   "filter": "IJAMT submission guidelines, quote q_width, retrieved 2026-09-22",
   "statistic": "value as printed"
  },
  "source": "q01_venue.py",
  "kind": "external"
 },
 "v_fig_width_col_mm": {
  "value": 84.0,
  "unit": "mm",
  "estimand": {
   "population": "external source",
   "filter": "IJAMT submission guidelines, quote q_width, retrieved 2026-09-22",
   "statistic": "value as printed"
  },
  "source": "q01_venue.py",
  "kind": "external"
 },
 "v_fig_width_page_mm": {
  "value": 174.0,
  "unit": "mm",
  "estimand": {
   "population": "external source",
   "filter": "IJAMT submission guidelines, quote q_width, retrieved 2026-09-22",
   "statistic": "value as printed"
  },
  "source": "q01_venue.py",
  "kind": "external"
 },
 "v_font_max_pt": {
  "value": 12,
  "unit": "pt",
  "estimand": {
   "population": "external source",
   "filter": "IJAMT submission guidelines, quote q_fontsize, retrieved 2026-09-22",
   "statistic": "value as printed"
  },
  "source": "q01_venue.py",
  "kind": "external"
 },
 "v_font_min_pt": {
  "value": 8,
  "unit": "pt",
  "estimand": {
   "population": "external source",
   "filter": "IJAMT submission guidelines, quote q_fontsize, retrieved 2026-09-22",
   "statistic": "value as printed"
  },
  "source": "q01_venue.py",
  "kind": "external"
 },
 "v_heading_levels_max": {
  "value": 3,
  "unit": "levels",
  "estimand": {
   "population": "external source",
   "filter": "IJAMT submission guidelines, quote q_headings, retrieved 2026-09-22",
   "statistic": "value as printed"
  },
  "source": "q01_venue.py",
  "kind": "external"
 },
 "v_ijamt_ref_share_max": {
  "value": 0.15,
  "unit": "fraction",
  "estimand": {
   "population": "external source",
   "filter": "IJAMT submission guidelines, quote q_ijamt15, retrieved 2026-09-22",
   "statistic": "value as printed"
  },
  "source": "q01_venue.py",
  "kind": "external"
 },
 "v_keywords_max": {
  "value": 6,
  "unit": "keywords",
  "estimand": {
   "population": "external source",
   "filter": "IJAMT submission guidelines, quote q_keywords, retrieved 2026-09-22",
   "statistic": "value as printed"
  },
  "source": "q01_venue.py",
  "kind": "external"
 },
 "v_keywords_min": {
  "value": 4,
  "unit": "keywords",
  "estimand": {
   "population": "external source",
   "filter": "IJAMT submission guidelines, quote q_keywords, retrieved 2026-09-22",
   "statistic": "value as printed"
  },
  "source": "q01_venue.py",
  "kind": "external"
 },
 "v_line_min_mm": {
  "value": 0.1,
  "unit": "mm",
  "estimand": {
   "population": "external source",
   "filter": "IJAMT submission guidelines, quote q_line, retrieved 2026-09-22",
   "statistic": "value as printed"
  },
  "source": "q01_venue.py",
  "kind": "external"
 },
 "v_orcid_digits": {
  "value": 16,
  "unit": "digits",
  "estimand": {
   "population": "external source",
   "filter": "IJAMT submission guidelines, quote q_orcid, retrieved 2026-09-22",
   "statistic": "value as printed"
  },
  "source": "q01_venue.py",
  "kind": "external"
 },
 "v_other_retrieved": {
  "value": "2026-09-22",
  "unit": "date",
  "estimand": {
   "population": "U1 article page and LaTeX author support page",
   "filter": "retrieval record",
   "statistic": "date read"
  },
  "source": "q01_venue.py",
  "kind": "text"
 },
 "v_page_chars": {
  "value": 48788,
  "unit": "characters",
  "estimand": {
   "population": "IJAMT submission guidelines",
   "filter": "document.body.innerText",
   "statistic": "characters"
  },
  "source": "q01_venue.py",
  "kind": "value"
 },
 "v_page_headings": {
  "value": 67,
  "unit": "headings",
  "estimand": {
   "population": "IJAMT submission guidelines",
   "filter": "page_headings",
   "statistic": "headings with text under them"
  },
  "source": "q01_venue.py",
  "kind": "value"
 },
 "v_quotes_checked": {
  "value": 109,
  "unit": "quotes",
  "estimand": {
   "population": "inputs/venue_checklist_quotes.json",
   "filter": "quote_check and quote_check_round2",
   "statistic": "quotes found verbatim on the page"
  },
  "source": "q01_venue.py",
  "kind": "value"
 },
 "v_quotes_checked_round2": {
  "value": 54,
  "unit": "quotes",
  "estimand": {
   "population": "inputs/venue_checklist_quotes.json",
   "filter": "quote_check_round2",
   "statistic": "quotes added after the review round and found verbatim on the page"
  },
  "source": "q01_venue.py",
  "kind": "value"
 },
 "v_quotes_failed": {
  "value": 0,
  "unit": "quotes",
  "estimand": {
   "population": "inputs/venue_checklist_quotes.json",
   "filter": "quote_check and quote_check_round2",
   "statistic": "quotes not found"
  },
  "source": "q01_venue.py",
  "kind": "value"
 },
 "v_referees": {
  "value": 2,
  "unit": "referees",
  "estimand": {
   "population": "external source",
   "filter": "IJAMT submission guidelines, quote q_reviewers, retrieved 2026-09-22",
   "statistic": "value as printed"
  },
  "source": "q01_venue.py",
  "kind": "external"
 },
 "v_retrieved_date": {
  "value": "2026-09-22",
  "unit": "date",
  "estimand": {
   "population": "IJAMT submission guidelines",
   "filter": "retrieval record",
   "statistic": "date the page was read (UTC)"
  },
  "source": "q01_venue.py",
  "kind": "text"
 },
 "v_rgb_bits": {
  "value": 8,
  "unit": "bits",
  "estimand": {
   "population": "external source",
   "filter": "IJAMT submission guidelines, quote q_rgb, retrieved 2026-09-22",
   "statistic": "value as printed"
  },
  "source": "q01_venue.py",
  "kind": "external"
 },
 "v_round2_date": {
  "value": "2026-09-23",
  "unit": "date",
  "estimand": {
   "population": "inputs/venue_checklist_quotes.json",
   "filter": "quote_check_round2",
   "statistic": "date of the second reading (UTC)"
  },
  "source": "q01_venue.py",
  "kind": "text"
 },
 "v_small_fig_height_mm": {
  "value": 195.0,
  "unit": "mm",
  "estimand": {
   "population": "external source",
   "filter": "IJAMT submission guidelines, quote q_small_width, retrieved 2026-09-22",
   "statistic": "value as printed"
  },
  "source": "q01_venue.py",
  "kind": "external"
 },
 "v_small_fig_width_mm": {
  "value": 119.0,
  "unit": "mm",
  "estimand": {
   "population": "external source",
   "filter": "IJAMT submission guidelines, quote q_small_width, retrieved 2026-09-22",
   "statistic": "value as printed"
  },
  "source": "q01_venue.py",
  "kind": "external"
 },
 "v_sn_latex_url": {
  "value": "https://www.springernature.com/gp/authors/campaigns/latex-author-support",
  "unit": "text",
  "estimand": {
   "population": "Springer Nature LaTeX author support page",
   "filter": "retrieval record",
   "statistic": "URL read"
  },
  "source": "q01_venue.py",
  "kind": "text"
 },
 "v_source_url": {
  "value": "https://link.springer.com/journal/170/submission-guidelines",
  "unit": "text",
  "estimand": {
   "population": "IJAMT submission guidelines",
   "filter": "retrieval record",
   "statistic": "URL read"
  },
  "source": "q01_venue.py",
  "kind": "text"
 },
 "v_submission_questions": {
  "value": 3,
  "unit": "questions",
  "estimand": {
   "population": "external source",
   "filter": "IJAMT submission guidelines, quote q_questions, retrieved 2026-09-22",
   "statistic": "value as printed"
  },
  "source": "q01_venue.py",
  "kind": "external"
 },
 "v_template_version": {
  "value": "December 2024",
  "unit": "text",
  "estimand": {
   "population": "external source",
   "filter": "Springer Nature LaTeX author support page, retrieved 2026-09-22",
   "statistic": "template package version as printed"
  },
  "source": "q01_venue.py",
  "kind": "external"
 },
 "v_template_zip_kb": {
  "value": 880.68,
  "unit": "KB",
  "estimand": {
   "population": "external source",
   "filter": "Springer Nature LaTeX author support page, retrieved 2026-09-22",
   "statistic": "package size as printed"
  },
  "source": "q01_venue.py",
  "kind": "external"
 },
 "v_u1_url": {
  "value": "https://link.springer.com/article/10.1007/s00170-026-18611-7",
  "unit": "text",
  "estimand": {
   "population": "IJAMT article page of U1",
   "filter": "retrieval record",
   "statistic": "URL read"
  },
  "source": "q01_venue.py",
  "kind": "text"
 },
 "winsor_q": {
  "value": 0.01,
  "unit": "fraction",
  "estimand": {
   "population": "analyst judgment",
   "filter": "Phase 3 plan",
   "statistic": "tail share clipped on each side of every feature in variant V5, with limits fitted on the training fold only"
  },
  "source": "q02_judgments.py",
  "kind": "judgment"
 },
 "words_main_max": {
  "value": 8000,
  "unit": "words",
  "estimand": {
   "population": "analyst judgment",
   "filter": "Phase 3 plan",
   "statistic": "self-imposed ceiling on the main text (title to conclusions, without references, tables, captions and declarations); the guidelines state no limit for original articles"
  },
  "source": "q02_judgments.py",
  "kind": "judgment"
 }
}