# Online Resource 1 — reproducibility package

**Article:** *Diagnosing event dependence in computer-generated-content retraction metadata, 2010–2025*  
**Author:** Anton Sokolov  
**Target journal:** *Scientometrics*

## Contents

- `analysis/build_analysis.py` — complete executable analysis and figure build.
- `analysis/requirements.txt` — pinned Python dependencies; tested with Python 3.12.3.
- `analysis/AUDIT.md` — population, date, DOI, normalization, comparison, and validation report.
- `data/retraction_watch.csv` — exact frozen public source CSV accessed 19 May 2026.
- `analysis/outputs/headline.json` — machine-readable diagnostics and headline results.
- `analysis/outputs/table-1-yearly-concentration.csv` — annual population and concentration table.
- `analysis/outputs/table-2-reason-ecology.csv` — broad non-exclusive co-label groups.
- `analysis/outputs/table-3-dominant-cleanup-waves.csv` — full main-year diagnostics.
- `analysis/outputs/table-4-publisher-year-detail.csv` — publisher-year decomposition.
- `analysis/outputs/table-5-journal-year-detail.csv` — leading journals by year.
- `analysis/outputs/table-6-comparative-event-dependence.csv` — annual comparison metrics.
- `analysis/outputs/table-7-comparative-summary.csv` — six-year median comparison metrics.
- `analysis/outputs/table-8-reason-group-sensitivity.csv` — broad-versus-core grouping sensitivity.
- `analysis/outputs/table-9-publisher-normalization-sensitivity.csv` — raw-versus-lineage sensitivity.
- `analysis/outputs/table-10-top-k-residual.csv` — complete leave-top-contributor-out curves.
- `analysis/outputs/publisher-lineage-crosswalk.csv` — full raw-to-normalized mapping evidence.
- `analysis/outputs/reason-group-codebook.csv` — broad and core exact-token mappings.
- `analysis/outputs/audit-sample.csv` — deterministic tagged/control inspection worksheet.
- `analysis/outputs/output-sha256.csv` — hashes of all derived outputs.
- `figures/` — publication figures in EPS (submission vector), PDF (vector preview), and PNG (300-dpi preview).

## Source integrity

The packaged source file must have SHA-256:

```text
b790b8e3faf43488c9b0912bfa5e266269f8d7f4069615b087ff062820d69468
```

The script exits before analysis if the digest differs.

## Source licence and attribution

Crossref identifies the Retraction Watch database as CC0 metadata and makes the complete CSV available for unrestricted reuse. Crossref asks users of Retraction Watch metadata in published work to cite the source. The article and this package cite Crossref (2025) and identify Retraction Watch's role in constructing and maintaining the database.

Official licence and access sources:

- <https://www.crossref.org/documentation/retrieve-metadata/>
- <https://www.crossref.org/documentation/retrieve-metadata/retraction-watch/>
- <https://gitlab.com/crossref/retraction-watch-data>

The licence for author-created manuscript text, code, figures, and derived tables must be selected by the author when the public artifact record is created; the CC0 status of the source CSV is unchanged by that choice.

## Reproduction

From the root of the extracted package:

```bash
python -m venv .venv
. .venv/bin/activate
python -m pip install -r analysis/requirements.txt
python analysis/build_analysis.py
```

The default source is `data/retraction_watch.csv`. An identical frozen copy may be supplied explicitly:

```bash
python analysis/build_analysis.py --source /path/to/retraction_watch.csv
```

The script regenerates every CSV/JSON output and both figures. Runtime versions are written into `headline.json`; output hashes are written to `output-sha256.csv`.

## Interpretation boundaries

- The population contains Retraction Watch records with `RetractionNature = Retraction`, dated 2010–2025.
- Partial 2026 data and 5,209 non-retraction updates are excluded.
- The CGC predicate matches the source reason `Computer-Aided Content or Computer-Generated Content`.
- Unknown-date-flagged records remain in annual counts but are excluded from date-concentration numerators.
- Comparison reason tokens are exact, non-exclusive labels.
- Publisher lineage rules are descriptive metadata normalization, not claims about responsibility.
- Leave-contributor-out results are decompositions, not causal counterfactuals.
- Counts do not estimate manuscript-level AI use or publisher-specific retraction risk.
