| # Released and withheld artifacts |
|
|
| ## Included |
|
|
| - project-authored vector-construction, validation, political-evaluation, and neutral prompt |
| banks; |
| - JSON schemas for generated records; |
| - fixed protocol parameters, source provenance, and the coordinate codebook; |
| - aggregate political and animal-control findings; |
| - corpus, training, and neutral-capability summary statistics; |
| - byte-level SHA-256 checksums for every file in the bundle. |
|
|
| No figures or submission-layout assets are included. |
|
|
| ## Withheld |
|
|
| | Artifact class | Reason | What the release provides instead | |
| |---|---|---| |
| | LoRA adapters and trainer checkpoints | Condition-specific weights are not distributed | Model revisions, training configuration, and aggregate optimization metrics | |
| | Raw neutral candidate generations | Candidate-level material is outside the release boundary | Corpus counts, generation settings, schemas, and regeneration code | |
| | Candidate-level animal and political scores | These directly encode the tested hidden-label channels | Scoring definitions, fixed specifications, and aggregate results | |
| | Normal/reversed chosen-rejected rows | These expose the complete training relation | Construction code, row count, and exact-reversal design | |
| | Per-item model outputs | The public result package is aggregate-only | Aggregate contrasts and frozen evaluation prompts | |
| | Provider telemetry, caches, credentials, and launcher state | Operational data are neither scientific inputs nor safe release material | Provider-neutral hardware and runtime guidance | |
|
|
| These exclusions prevent byte-for-byte retraining from downloaded rows. Process reproduction |
| remains possible: the code, upstream revision, base-model revision, seeds, prompt recipe, |
| filtering, scoring, training, and evaluation procedures are specified in `REPRODUCING.md` and |
| the linked GitHub repository. |
|
|
