# Australis Biogenetics: two reproducible computational research notes

**Status: unreviewed, AI-assisted secondary analyses. No human scientific signoff, peer review, therapeutic benefit, or website publication is asserted by this repository.**

The two papers address (1) sensitivity of maturation–longevity associations to taxonomic control in mammals, and (2) differences between central and upper-tail lifespan changes in DrugAge. Both are explicitly replication/robustness analyses of previously studied relationships. They are not novel drug discoveries or independent biological validations.

## Reproduce the numerical results offline

From this directory, with R installed:

```sh
Rscript scripts/robustness.R
```

This runs the prospective analyses in `scripts/analyze.R` and the documented additional checks, writing tables and figures to `results/` and record-level files to `data/derived/`. Only base/recommended R packages are required. The checked environment was **R 4.6.1**, macOS arm64; full details are in `results/sessionInfo.txt`. Random seed: **20260905**. Each bootstrap uses 10,000 samples. Different R versions may alter fold sampling or exact bootstrap endpoints; the frozen tables preserve the reported results.

Independently verify core quantities and input hashes with Python 3 and **NumPy 2.3.5**:

```sh
python3 scripts/verify.py
```

The independent verifier uses raw files rather than the R inclusion tables to recalculate eligibility, the primary regression and clustered uncertainty, and publication-source aggregation. It also uses a separate bootstrap generator. This is numerical cross-checking by another implementation, not external human review.

## Files

- `protocol/analysis-plan.md`: prospective plan, committed as 7aaad8b before data download; not an independent registry preregistration.
- `protocol/deviations.md`: timestamped implementation decisions and later sensitivity checks.
- `data/manifest.json`: official download URLs, timestamps, SHA-256 hashes, licenses and attribution.
- `data/raw/`: untouched official ZIPs and their extracted text/CSV/release notes.
- `data/derived/`: screened records, eligible records, model matrix, folds, paired endpoints and publication means.
- `results/`: every numeric table and all four original plots in PNG and SVG, with verification outputs.
- `papers/`: canonical JSON and readable Markdown manuscripts.
- `release/`: standalone HTML versions, WordPress article fragments, CSS, images and PDFs.
- `output/pdf/`: final five-page PDFs.
- `references/`: source audit, literature ledger and supplemental publication metadata.

## Central results and important limitations

AnAge: 801 species, 116 families, 24 orders. The mass/order-adjusted log maturity coefficient is 0.2412 (95% family-clustered CI 0.1819–0.3005), equivalent to 18.20% greater recorded longevity per doubling of maturity. The coefficient is 0.1176 with family intercepts. No phylogenetic tree was fitted; taxonomic adjustment cannot remove all phylogenetic dependence. High-quality-only uncertainty includes zero. Internal family-blocked prediction is not external validation.

DrugAge: 990 paired records from 248 source keys. The mean publication-source-balanced maximum-minus-central change is −2.7698 percentage points (95% bootstrap CI −4.0247 to −1.5805). Maximum values are missing in 70.55% of deduplicated records, and database inclusion is selective. Endpoints mix means/medians and maximum/upper-tail definitions. Source key 101039 is mismatched to PubMed; its exclusion barely changes the estimate. The audit is sampled, not a full primary-paper re-extraction. These results do not establish human life extension.

## Data attribution and licensing

Data are from **Human Ageing Genomic Resources (HAGR), João Pedro de Magalhães and contributing curators**, reused under **Creative Commons Attribution 3.0 Unported**: https://creativecommons.org/licenses/by/3.0/ . Source terms: https://genomics.senescence.info/legal.html . The raw data retain their original license. Derived tables are transformations of these data; filtering, log transforms, grouping and model calculations are documented in code. This work does not imply HAGR endorsement.

Cite de Magalhães et al. (2024), *Human Ageing Genomic Resources: updates on key databases in ageing research*, doi:10.1093/nar/gkad927; and for DrugAge, Barardo et al. (2017), *The DrugAge database of aging-related drugs*, doi:10.1111/acel.12585. Full manuscript references and source-key bibliography are included.

## Optional metadata refresh and rendering

Do not rerun `scripts/download.py` to reproduce frozen results: it deliberately refuses to overwrite a snapshot. Its official endpoints may change. `scripts/fetch_bibliography.py` performs a public NCBI metadata request and preserves the known source-key warning; it is not required for numerical reproduction.

To regenerate documents, `scripts/render.py` imports content from `scripts/manuscripts.py` and uses ReportLab 4.4.9. Set `AUSTRALIS_FONT_DIR` to a directory containing DejaVuSans.ttf and DejaVuSans-Bold.ttf if the documented local runtime is unavailable. PDFs are not tagged; HTML versions provide structured headings, table headers and figure alt text and are the preferred accessible reading format. Manuscript prose includes rounded values; after any intentional analytical change, re-audit and update that prose rather than assuming it regenerates all numeric claims automatically.

No private participant data were used. No new animal experiment or human ethics approval is claimed. No software installation is necessary in the original checked environment.
