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67 lines
2.8 KiB
Markdown
67 lines
2.8 KiB
Markdown
# Engine-selection fixture set
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This directory is the tracked, content-balanced input set for researching a
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deterministic `auto` engine choice. It is not a training corpus and it is not a
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watermark-oracle corpus.
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## Content matrix
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`content-manifest.csv` contains 19 prompt-matched pairs. Each pair uses the
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same prompt and generation index across OpenAI `gpt-image-1-mini` and Meta
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`muse-image-1.0`, covering the content classes that materially stress image
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regeneration:
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- natural and urban scenes;
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- single-person portraits and people in context;
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- animals, food, products, interiors, architecture, macro detail, and action;
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- flat, isometric, watercolor, and surreal illustration styles.
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The files are exact copies of generation outputs collected for the
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`docs/arxiv-paper-review` research branch. The manifest records the SHA-256 of
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the committed bytes. The old OpenAI collection manifest stored the API payload
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hash under `sha256`; `source_payload_sha256` preserves that value while
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`sha256` always means the actual file bytes here. Meta's two hashes are the
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same.
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The project maintainer has cleared these exact committed outputs for permanent
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public test and benchmark reuse. `reuse_basis` records that clearance on every
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row. It is permission for this fixed fixture set, not a claim that either
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provider grants a general-purpose dataset license for arbitrary generations.
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One generation per prompt and provider is enough for the first paired
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discovery pass. Any policy inferred from it must be challenged against unused
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generation indices from the local research archive before shipping. Generated
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outputs belong outside this directory.
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`carrier-manifest.csv` adds the canonical, already tracked signal carriers to
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the study without copying their bytes. Together the two manifests cover
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ordinary content, text, single faces, face grids, and mixed face/text scenes.
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## Signal carriers
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The content matrix was re-encoded by its collection pipeline and has no local
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provenance signal. It must not be used to set or certify watermark-removal
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strengths. The tracked oracle/carrier inputs remain in their canonical homes:
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- OpenAI and Google SynthID: `data/synthid/originals/` with
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`data/synthid/manifest.csv`;
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- Meta Content Seal: `data/contentseal/originals/` with
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`data/contentseal/manifest.csv`.
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There is no tracked, publication-cleared Microsoft InvisMark carrier yet. The
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three Paint sources used by the earlier calibration are user uploads and remain
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outside git. A Microsoft row may be added only from a newly generated or
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otherwise publication-cleared source, with a pixel-identical metadata-stripped
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control that remains positive in Microsoft's detector.
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## Integrity check
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Run:
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```bash
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uv run python scripts/verify_engine_selection_fixtures.py
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```
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The check validates paths, byte hashes, dimensions, prompt pairing, and the
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declared provider/content matrix without loading any ML model.
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