# <Paper title>

Analysis code and data for: <authors> (<year>). <title>. <venue>.
Preprint: <doi> / Archived release: <zenodo/osf doi>

## What's here

    analysis/     numbered pipeline scripts (01_clean.py ... 04_check.py)
    data/         raw data (or fetch instructions; see below)
    results/      regenerated by the pipeline; not committed
    figures/      regenerated by the pipeline; not committed
    pyproject.toml + uv.lock   exact software environment
    Makefile      one-command runner (`make all`)

## Reproduce the results

Requires: [uv](https://docs.astral.sh/uv/) >= 0.7, GNU make.
Tested on: macOS 15.5 and Ubuntu 24.04, ~4 minutes, < 2 GB RAM.

    git clone <repo-url> && cd <repo>
    make all        # regenerates results/ and figures/ from raw data
    make check      # asserts every number claimed in the paper

Expected final line: `all published values reproduced`

## Data

- `data/raw.csv`: <description>. SHA-256: `<checksum>`.
- <If restricted: exactly who can access it, how to request it, and what
  synthetic/subset stand-in is included so the pipeline still runs.>

## Randomness and tolerances

All analyses seed their generators (seeds recorded in the scripts).
Stochastic results (bootstrap CIs) are bit-exact given the seed and stable
to +/-0.05 across seeds; `make check` enforces the reported tolerances.

## Environment notes

Python 3.12.3, dependencies locked in `uv.lock`. A container image is
archived with the release for long-term execution:
`docker load < rt-study-v1-image.tar.gz`.

## License and citation

Code: MIT. Data: <license>. Please cite the paper above; this repository's
archived DOI is <doi>.