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AI Purity Detection Algorithm v0.2\n\n**Status:** Draft v0.2  \n**Repository:** `ai-purity-detection-algorithm-v0.2`  \n**Version:** 0.2.2\n\nAI Purity Detection Algorithm v0.2 is a draft specification for estimating origin purity, AI-generated ratio, warning flags, recursive synthetic risk, and review routing in AI source-preservation systems.\n\nThis repository focuses on the algorithmic layer of source preservation.\n\nIt is designed to support:\n\n- origin-purity scoring\n- natural / synthetic data separation\n- hybrid data classification\n- recursive synthetic risk detection\n- warning-flag severity modeling\n- review-required routing\n- model-collapse monitoring\n- royalty-readiness review\n- meaning-structure relationship review\n- platform UI integration patterns\n- future Purity UI control architecture\n- future API-based implementation\n\nThe goal is not to reject AI-assisted creation.\n\nThe goal is to preserve the source ecology of AI civilization.\n\n---\n\n## Concept\n\nAI systems increasingly depend on human-created and AI-assisted sources.\n\nThese sources may include:\n\n- articles\n- books\n- notes\n- datasets\n- protocols\n- essays\n- research logs\n- structural concepts\n- firsthand observations\n- AI-assisted drafts\n- recursively rewritten synthetic material\n\nAs AI systems summarize, rewrite, remix, and reuse these sources, the origin of a source can become difficult to identify.\n\nThis creates several risks:\n\n- primary sources become invisible\n- synthetic data begins to replace natural data\n- AI systems consume recursively generated outputs\n- model-collapse risk increases\n- creators lose traceability\n- reference auditing becomes difficult\n- royalty-readiness review becomes unreliable\n- meaning structures become shallow or generic\n- platform interfaces fail to show origin context\n- creator-controlled disclosure boundaries remain underdeveloped\n\nAI Purity Detection Algorithm v0.2 proposes a review-aware scoring and warning model for these risks.\n\n---\n\n## Core Principle\n\nPurity is not a moral judgment.\n\n```text\nPurity ≠ Value\nPurity ≠ Copyright\nPurity ≠ Authorship\nPurity = estimated origin composition\n```\n\nA work may be AI-assisted and still contain strong human originality.\n\nA work may be human-written and still be derivative, weakly sourced, or structurally shallow.\n\nThe purpose of this specification is not to decide who deserves value.\n\nThe purpose is to help systems distinguish:\n\n- source\n- summary\n- derivative\n- synthetic output\n- recursive synthetic loop\n- structurally original hybrid work\n\n---\n\n## Design Philosophy\n\nAI-assisted creation should not be treated as invalid by default.\n\nInstead, the system should ask:\n\n```text\nCan the origin be traced?\nIs the structure original?\nIs the source chain clear?\nIs the AI-generated ratio high?\nIs recursive synthetic risk present?\nIs review required before downstream use?\nCan the creator control disclosure boundaries?\nCan platform UI preserve the origin context?\n```\n\nThis repository treats purity assessment as a support layer for review, governance, platform design, and ecosystem health.\n\nIt does not attempt to automate legal, financial, or moral judgment.\n\n---\n\n## v0.2 Focus\n\nVersion `v0.2` expands the purity assessment layer from a basic schema-validated object into a more explicit algorithmic, review-routing, relationship-aware, and platform-integration model.\n\nThe main v0.2 focus areas are:\n\n```text\nsignal weighting\nconfidence adjustment\nwarning-flag severity\nrecursive synthetic risk detection\nreview routing\ndownstream-use guidance\nCollapseMonitor bridge\nRoyalty Readiness bridge\nConsciousness Circle bridge\nplatform UI integration mock\nfuture Purity UI evolution roadmap\nAPI design notes\n```\n\nIn short:\n\n```text\nv0.1 = minimum valid purity assessment\nv0.2 = weighted, review-aware, risk-sensitive purity assessment model\nv0.2.1 = platform UI integration reference added\nv0.2.2 = Purity UI v0.3 evolution roadmap added\n```\n\n---\n\n## Repository Structure\n\n```text\n.\n├── README.md\n├── CHANGELOG.md\n├── CITATION.cff\n├── LICENSE\n├── docs/\n│   ├── v0.2-roadmap.md\n│   ├── scoring-weighting-model.md\n│   ├── warning-flag-severity-model.md\n│   ├── relationship-to-consciousness-circle.md\n│   ├── relationship-to-royalty-readiness.md\n│   ├── relationship-to-collapse-monitor.md\n│   ├── api-design-notes.md\n│   ├── ui-mock-note-integration.md\n│   └── purity-ui-evolution-roadmap-v0.3.md\n├── schemas/\n│   └── purity-assessment.schema.json\n├── examples/\n│   ├── purity-assessment.sample.yaml\n│   ├── purity-assessment.low-confidence.sample.yaml\n│   └── purity-assessment.recursive-synthetic-risk.sample.yaml\n└── .github/\n    └── workflows/\n        └── validate-examples.yml\n```\n\n### Directory Overview\n\n- `docs/`  \n  Explanatory documents, relationship notes, scoring models, warning-severity models, API design notes, platform UI mock references, and future UI evolution roadmap documents.\n\n- `schemas/`  \n  JSON Schema definitions for validating Purity assessment objects.\n\n- `examples/`  \n  YAML examples showing standard, low-confidence, and recursive synthetic-risk assessment cases.\n\n- `.github/workflows/`  \n  GitHub Actions workflow for validating examples against the schema.\n\n---\n\n## Key Documents\n\n### `docs/v0.2-roadmap.md`\n\nDefines the proposed direction for AI Purity Detection Algorithm v0.2.\n\nIt outlines:\n\n- v0.1 baseline\n- v0.2 design goals\n- signal weighting\n- confidence handling\n- warning-flag severity\n- recursive synthetic risk detection\n- review routing\n- relationship to CollapseMonitor\n- relationship to Royalty Readiness\n\n---\n\n### `docs/scoring-weighting-model.md`\n\nDefines the draft scoring model for calculating `origin_purity_score`.\n\nIt introduces the main signal variables:\n\n```text\nP = provenance_evidence_score\nD = author_declaration_score\nU = structural_originality_score\nR = revision_lineage_score\nC = citation_transparency_score\nG = ai_pattern_risk_score\nF = structure_fingerprint_distinctiveness_score\nS = recursive_synthetic_risk_score\nQ = signal_confidence_quality_score\n```\n\nIt also defines:\n\n- default signal weights\n- confidence adjustment\n- recursive risk adjustment\n- interpretation bands\n- review-routing thresholds\n- downstream-use guidance\n\n---\n\n### `docs/warning-flag-severity-model.md`\n\nDefines how warning flags should be interpreted.\n\nIt introduces four severity levels:\n\n```text\ninfo\nwarning\nreview_required\nblocking\n```\n\nIt explains how warning flags affect:\n\n- review routing\n- downstream use\n- royalty-readiness transition\n- collapse monitoring\n- uncertainty handling\n\nThe key principle is:\n\n```text\nWarning flags are routing signals.\nThey are not court verdicts.\n```\n\n---\n\n### `docs/relationship-to-consciousness-circle.md`\n\nExplains how AI Purity Detection relates to Consciousness Circle.\n\nThis document distinguishes:\n\n```text\nPurity Detection = data-origin layer\nConsciousness Circle = meaning-origin layer\n```\n\nIt explores how origin purity may connect to:\n\n- meaning depth\n- initial friction\n- resonance quality\n- boundary stability\n- consciousness-like response structure\n- synthetic meaning risk\n- creator-controlled disclosure\n\nIt does not claim that AI has consciousness.\n\nIt defines a relationship between source integrity and meaning integrity.\n\n---\n\n### `docs/relationship-to-royalty-readiness.md`\n\nExplains how purity assessment supports Royalty Readiness.\n\nThis document clarifies that:\n\n```text\norigin_purity_score\n≠\nroyalty entitlement\n```\n\nPurity assessment may support:\n\n- readiness review\n- warning severity review\n- trace evidence review\n- blocked-state handling\n- disputed-state handling\n- allocation-preparation logic\n\nIt does not define final royalty rates, payment, or legal ownership.\n\n---\n\n### `docs/relationship-to-collapse-monitor.md`\n\nExplains how source-level purity assessments may support CollapseMonitor.\n\nThis document defines the relationship between:\n\n```text\nPurity Detection = local source assessment\nCollapseMonitor = systemic health monitoring\n```\n\nIt outlines possible aggregate metrics such as:\n\n- natural-data ratio\n- synthetic-data ratio\n- recursive synthetic risk rate\n- missing provenance rate\n- low-confidence assessment rate\n- review-required rate\n- training-use blocked rate\n- collapse-risk score\n- civilization-health index\n\nIt does not define a production-ready CollapseMonitor implementation.\n\n---\n\n### `docs/api-design-notes.md`\n\nOutlines possible API design for future implementation.\n\nIt includes preliminary notes on:\n\n- core API objects\n- proposed endpoints\n- purity assessment submission\n- assessment retrieval\n- batch assessment\n- source history\n- review routing\n- aggregate health signals\n- safety rules\n- error handling\n- access control\n- privacy considerations\n- relationship to Trace Protocol\n- relationship to CollapseMonitor\n- relationship to Royalty Readiness\n- relationship to Consciousness Circle\n\nThis document is a design bridge, not a production API specification.\n\n---\n\n### `docs/ui-mock-note-integration.md`\n\nProvides a platform UI mock showing how Purity metadata could be integrated into a note-style article page.\n\nIt connects:\n\n- Purity Badge\n- Purity Breakdown\n- Consciousness Circle Panel\n- Trace Log\n- Royalty OS Preview\n- Creator Controls\n\nThis document translates the v0.2 specification from an algorithmic layer into a possible platform-facing interface.\n\nIt is a reference design, not a mandatory implementation standard.\n\nThe core purpose is to show how an article page could evolve from a simple content display into a creator-controlled semantic origin interface.\n\n---\n\n### `docs/purity-ui-evolution-roadmap-v0.3.md`\n\nProvides a future roadmap for evolving Purity UI beyond a score display or basic platform mock.\n\nIt introduces possible v0.3 design directions, including:\n\n- Epicenter Layer\n- Proto-Friction Layer\n- Visibility Protocol\n- Circle Versioning\n- No-Inference Layer\n- Royalty OS Visibility\n- Epicenter Network\n\nThis document is not a final specification.\n\nIt is a roadmap for exploring how Purity UI may evolve into a creator-controlled origin interface and, eventually, a separate Purity UI Control Architecture.\n\nPossible future repository:\n\n```text\npurity-ui-control-architecture-v0.1\n```\n\n---\n\n### `schemas/purity-assessment.schema.json`\n\nProvides a JSON Schema for validating purity assessment outputs.\n\nThe schema validates:\n\n- required fields\n- score ranges\n- warning flags\n- review status\n- downstream-use permissions\n- optional v0.2 extensions\n- ISO 8601 date-time format for `assessed_at`\n\n---\n\n## Examples\n\n### `examples/purity-assessment.sample.yaml`\n\nA standard purity assessment example.\n\nThis sample demonstrates:\n\n- strong provenance\n- high structural originality\n- moderate AI assistance\n- review recommendation\n- RAG suitability\n- conditional training use\n- royalty-readiness review state\n\n---\n\n### `examples/purity-assessment.low-confidence.sample.yaml`\n\nA low-confidence example.\n\nThis sample demonstrates:\n\n- weak provenance\n- unclear origin\n- incomplete signal coverage\n- low confidence\n- review-required routing\n- blocked royalty readiness\n\nThis example is important because the system must be able to say:\n\n```text\nThe evidence is not strong enough.\nReview is required.\n```\n\n---\n\n### `examples/purity-assessment.recursive-synthetic-risk.sample.yaml`\n\nA recursive synthetic risk example.\n\nThis sample demonstrates:\n\n- weak primary-source provenance\n- high AI-pattern similarity\n- low structural originality\n- likely recursive AI rewriting\n- blocked training use\n- blocked royalty readiness\n- high-priority CollapseMonitor signal\n\nThis example represents the core risk that the purity layer is designed to detect:\n\n```text\nAI systems consuming recursively generated synthetic material.\n```\n\n---\n\n## Validation\n\nThis repository includes a GitHub Actions workflow for validating example files against the JSON Schema.\n\nThe workflow is defined in:\n\n```text\n.github/workflows/validate-examples.yml\n```\n\nCurrent validation targets:\n\n```text\nexamples/purity-assessment.sample.yaml\nexamples/purity-assessment.low-confidence.sample.yaml\nexamples/purity-assessment.recursive-synthetic-risk.sample.yaml\n↓\nschemas/purity-assessment.schema.json\n```\n\nThe workflow checks that each sample purity assessment object conforms to the schema definition, including:\n\n- required fields\n- score ranges from `0.0` to `1.0`\n- allowed `method` values\n- allowed `warning_flags`\n- review status structure\n- downstream-use permission structure\n- ISO 8601 date-time format for `assessed_at`\n\nThe validation workflow uses:\n\n```text\nPython 3.12\njsonschema\nPyYAML\n```\n\nThe validation process is:\n\n```text\nLoad YAML examples\n↓\nLoad JSON Schema\n↓\nValidate each example against schema\n↓\nReport pass / fail\n```\n\nIf validation fails, the workflow prints the failing field path and schema error.\n\n---\n\n## Core Output Fields\n\nA purity assessment produces three core outputs.\n\n### `origin_purity_score`\n\nA normalized score from `0.0` to `1.0`.\n\nIt estimates whether a source appears to be:\n\n- primary-origin\n- human-primary\n- hybrid\n- synthetic-heavy\n- recursively synthetic\n- origin-unclear\n\nSuggested interpretation:\n\n```text\n0.90 – 1.00 : strong primary-origin signal\n0.70 – 0.89 : likely human-primary or structurally original\n0.50 – 0.69 : hybrid / uncertain / review recommended\n0.30 – 0.49 : likely synthetic-heavy or derivative\n0.00 – 0.29 : low-origin / recursive synthetic risk\n```\n\n---\n\n### `ai_generated_ratio`\n\nA normalized estimate from `0.0` to `1.0`.\n\nIt estimates the likely proportion of AI-generated or AI-assisted material.\n\nImportant:\n\n```text\nHigh AI-generated ratio does not automatically mean low value.\nLow AI-generated ratio does not automatically mean high originality.\n```\n\nThis field should be interpreted together with provenance, structural originality, confidence, and review status.\n\n---\n\n### `warning_flags`\n\nWarning flags identify uncertainty, risk, or review requirements.\n\nCurrent warning flags include:\n\n```text\nmissing_provenance\nhigh_ai_pattern_similarity\ndeclaration_conflict\nlow_confidence_score\nrecursive_synthetic_risk\norigin_unclear\nreview_required\nreview_recommended\nroyalty_readiness_blocked\n```\n\nWarning flags should not be treated as automatic rejection.\n\nThey indicate what kind of attention is needed.\n\n---\n\n## Scoring Model Overview\n\nThe v0.2 draft scoring model uses weighted input signals.\n\nDraft base formula:\n\n```text\nbase_origin_purity_score =\n  0.20P\n+ 0.10D\n+ 0.20U\n+ 0.10R\n+ 0.10C\n+ 0.10(1 - G)\n+ 0.10F\n+ 0.10(1 - S)\n```\n\nWhere:\n\n```text\nP = provenance evidence score\nD = author declaration score\nU = structural originality score\nR = revision lineage score\nC = citation transparency score\nG = AI pattern risk score\nF = structure fingerprint distinctiveness score\nS = recursive synthetic risk score\n```\n\nThe model may then apply:\n\n```text\nconfidence_adjustment\nrecursive_risk_adjustment\n```\n\nFinal form:\n\n```text\norigin_purity_score =\n  base_origin_purity_score\n  × confidence_adjustment\n  × recursive_risk_adjustment\n```\n\nThe goal is not mathematical complexity.\n\nThe goal is auditability.\n\n---\n\n## Warning Severity Overview\n\nWarning flags may be classified into severity levels.\n\n```text\ninfo\n↓\ncontext only\n\nwarning\n↓\ncaution / review recommended\n\nreview_required\n↓\nreview needed before high-impact use\n\nblocking\n↓\nautomatic downstream transition blocked\n```\n\nExample mapping:\n\n```text\nmissing_provenance              → review_required\nhigh_ai_pattern_similarity      → warning\ndeclaration_conflict            → review_required\nlow_confidence_score            → review_required\nrecursive_synthetic_risk        → review_required / blocking\norigin_unclear                  → review_required\nreview_recommended              → warning\nroyalty_readiness_blocked       → blocking\n```\n\n---\n\n## Review Routing\n\nThe v0.2 model supports review routing.\n\nSuggested review modes:\n\n```text\nnone\nrecommended\nrequired\nblocking_review\n```\n\nReview may be triggered by:\n\n- low confidence\n- missing provenance\n- recursive synthetic risk\n- origin unclear\n- declaration conflict\n- royalty-readiness request\n- high downstream impact\n- blocked training use\n\nThis prevents the system from making premature judgments when evidence is weak.\n\n---\n\n## Downstream Use Guidance\n\nPurity assessment may support downstream decisions, but it should not automatically decide them.\n\n### RAG Indexing\n\nMay be allowed when provenance and warning status are acceptable.\n\n### Training Use\n\nShould require stronger provenance, permission, and policy compatibility.\n\n### Royalty Readiness\n\nShould not be determined solely by purity score.\n\nA high purity score may support review readiness.\n\nA low or uncertain score should trigger review.\n\nA blocking flag should prevent automatic transition.\n\n### Collapse Monitoring\n\nAggregated purity results may support model-collapse risk monitoring.\n\nUseful aggregate metrics include:\n\n- average origin purity\n- synthetic-data ratio\n- hybrid-data ratio\n- recursive synthetic risk rate\n- low-confidence assessment rate\n- review-required rate\n- blocked royalty-readiness rate\n\n### Platform UI Integration\n\nPurity metadata may also support platform-facing displays.\n\nPossible UI elements include:\n\n- Purity Badge\n- Purity Breakdown\n- Consciousness Circle summary\n- Trace visibility panel\n- Royalty OS preview\n- Creator disclosure controls\n\nThese UI elements should remain creator-controlled and should not expose private semantic context by default.\n\nSee:\n\n```text\ndocs/ui-mock-note-integration.md\n```\n\n### Future UI Control Architecture\n\nFuture versions may explore how Purity UI evolves from a display layer into a creator-controlled origin interface.\n\nPossible future UI-control concepts include:\n\n- Epicenter Layer\n- Proto-Friction Layer\n- Visibility Protocol\n- Circle Versioning\n- No-Inference Layer\n- Royalty OS Visibility\n- Epicenter Network\n\nSee:\n\n```text\ndocs/purity-ui-evolution-roadmap-v0.3.md\n```\n\n---\n\n## Relationship Map\n\nAI Purity Detection Algorithm v0.2 connects to multiple surrounding systems.\n\n```text\nTrace Protocol\n↓\nPurity Assessment\n↓\nWarning Severity\n↓\nReview Routing\n↓\nRoyalty Readiness\n```\n\n```text\nPurity Assessment\n↓\nAggregate Metrics\n↓\nCollapseMonitor\n↓\nModel / Corpus / Civilization Health Signals\n```\n\n```text\nPurity Assessment\n+\nConsciousness Circle\n↓\nSource Integrity\n+\nMeaning Integrity\n```\n\n```text\nPurity Assessment\n↓\nAPI Layer\n↓\nExternal Systems\n```\n\n```text\nPurity Assessment\n+\nConsciousness Circle\n+\nTrace Log\n+\nCreator Controls\n↓\nPlatform UI Integration\n```\n\n```text\nPlatform UI Integration\n+\nVisibility Protocol\n+\nNo-Inference Layer\n+\nCircle Versioning\n↓\nFuture Purity UI Control Architecture\n```\n\n---\n\n## Relationship to Consciousness Circle\n\nThis repository evaluates data-origin integrity.\n\nConsciousness Circle evaluates meaning-origin and response-structure integrity.\n\nTogether, they support a deeper review model:\n\n```text\norigin purity\n+\nmeaning depth\n+\ninitial friction\n+\nresonance quality\n+\ncreator-controlled disclosure\n```\n\nThe key distinction is:\n\n```text\nOrigin purity alone is not meaning.\nMeaning depth alone is not provenance.\n```\n\n---\n\n## Relationship to Royalty Readiness\n\nPurity assessment may support Royalty Readiness, but must not directly determine payment.\n\n```text\nPurity Detection does not pay.\nPurity Detection prepares the evidence.\nRoyalty Readiness decides whether review can begin.\n```\n\nRecommended flow:\n\n```text\nPurity Assessment\n↓\nTrace Evidence\n↓\nWarning Severity\n↓\nReview Routing\n↓\nRoyalty Readiness\n↓\nAllocation Review\n```\n\n---\n\n## Relationship to CollapseMonitor\n\nThis repository evaluates individual source-level purity.\n\nCollapseMonitor would evaluate ecosystem-level risk.\n\n```text\nPurity Detection\n↓\nAggregate Metrics\n↓\nCollapseMonitor\n↓\nModel / Corpus / Civilization Health Signals\n```\n\nPossible future repository:\n\n```text\ncollapse-monitor-threshold-model-v0.1\n```\n\n---\n\n## Relationship to Platform UI Integration\n\nPurity assessment can be used not only as a backend review signal, but also as a platform-facing origin-preservation interface.\n\nThe UI integration layer may show:\n\n```text\nPurity Badge\n↓\nPurity Breakdown\n↓\nConsciousness Circle Panel\n↓\nTrace Log\n↓\nRoyalty OS Preview\n↓\nCreator Controls\n```\n\nThe purpose is not to rank creators by purity.\n\nThe purpose is to help platforms show whether a work preserves a meaningful human-origin epicenter and whether the creator controls the disclosure boundary.\n\nSee:\n\n```text\ndocs/ui-mock-note-integration.md\n```\n\n---\n\n## Future Extensions\n\nThis repository may later connect to or seed future specifications.\n\nPossible future directions include:\n\n### Purity UI Control Architecture\n\nA future repository may define a dedicated control architecture for Purity UI.\n\nPossible repository name:\n\n```text\npurity-ui-control-architecture-v0.1\n```\n\nThis future work may include:\n\n- creator-controlled visibility settings\n- no-inference policies\n- circle versioning\n- proto-friction capture\n- epicenter network visualization\n- royalty-readiness UI\n- AI-readable disclosure boundaries\n\nThe current roadmap is documented in:\n\n```text\ndocs/purity-ui-evolution-roadmap-v0.3.md\n```\n\n### CollapseMonitor Threshold Model\n\nA future repository may define aggregate thresholds for ecosystem-level collapse-risk monitoring.\n\nPossible repository name:\n\n```text\ncollapse-monitor-threshold-model-v0.1\n```\n\n### Royalty Readiness Review Layer\n\nA future repository may define a more formal review layer between trace evidence and allocation review.\n\n### Platform API Profile\n\nA future repository or document may define an implementation-oriented API profile for Purity assessment, creator controls, and platform UI integration.\n\n---\n\n## API Design Direction\n\nThe API layer should expose:\n\n- source input\n- purity assessment\n- origin-purity score\n- AI-generated ratio\n- warning flags\n- recursive synthetic risk\n- review routing\n- downstream-use guidance\n- aggregate health signals\n- optional UI-facing metadata\n- creator disclosure settings\n\nThe API should not make final legal, financial, or moral decisions.\n\nThe central API principle is:\n\n```text\nExpose evidence.\nExpose uncertainty.\nExpose review routing.\nDo not expose premature judgment as final truth.\n```\n\n---\n\n## Non-Goals\n\nThis repository does not attempt to:\n\n- prove legal authorship\n- determine copyright ownership\n- automatically assign royalties\n- ban AI-assisted creation\n- punish synthetic content\n- perfectly detect AI-generated text\n- replace human or multi-wing review\n- define universal originality\n- prove AI consciousness\n- make moral judgments about creators\n- force disclosure of private creator context\n- rank creators by purity score\n- define a final platform UI standard\n- define a production-ready Purity UI Control Architecture\n\nThis is a review-support, platform-guidance, and ecosystem-health specification.\n\n---\n\n## Recommended Reading Order\n\nFor readers who want to understand this repository step by step, the following order is recommended.\n\n```text\n1. README.md\n2. docs/v0.2-roadmap.md\n3. docs/scoring-weighting-model.md\n4. docs/warning-flag-severity-model.md\n5. examples/purity-assessment.sample.yaml\n6. examples/purity-assessment.low-confidence.sample.yaml\n7. examples/purity-assessment.recursive-synthetic-risk.sample.yaml\n8. schemas/purity-assessment.schema.json\n9. docs/relationship-to-consciousness-circle.md\n10. docs/relationship-to-royalty-readiness.md\n11. docs/relationship-to-collapse-monitor.md\n12. docs/api-design-notes.md\n13. docs/ui-mock-note-integration.md\n14. docs/purity-ui-evolution-roadmap-v0.3.md\n15. .github/workflows/validate-examples.yml\n```\n\n### Reading Path by Role\n\n#### For general readers\n\n```text\nREADME.md\n↓\ndocs/v0.2-roadmap.md\n↓\ndocs/ui-mock-note-integration.md\n↓\ndocs/purity-ui-evolution-roadmap-v0.3.md\n```\n\n#### For implementers\n\n```text\nREADME.md\n↓\nschemas/purity-assessment.schema.json\n↓\nexamples/\n↓\ndocs/api-design-notes.md\n```\n\n#### For reviewers and governance designers\n\n```text\ndocs/scoring-weighting-model.md\n↓\ndocs/warning-flag-severity-model.md\n↓\ndocs/relationship-to-royalty-readiness.md\n↓\ndocs/relationship-to-collapse-monitor.md\n```\n\n#### For platform designers\n\n```text\ndocs/relationship-to-consciousness-circle.md\n↓\ndocs/api-design-notes.md\n↓\ndocs/ui-mock-note-integration.md\n↓\ndocs/purity-ui-evolution-roadmap-v0.3.md\n```\n\n#### For future UI-control architecture designers\n\n```text\ndocs/ui-mock-note-integration.md\n↓\ndocs/purity-ui-evolution-roadmap-v0.3.md\n```\n\n---\n\n## Version History\n\nSee:\n\n```text\nCHANGELOG.md\n```\n\nCurrent release:\n\n```text\n0.2.2\n```\n\n---\n\n## Citation\n\nIf you use this specification, please cite it using:\n\n```text\nCITATION.cff\n```\n\n---\n\n## License\n\nThis repository is released under the license defined in:\n\n```text\nLICENSE\n```\n\n---\n\n## Summary\n\nAI Purity Detection Algorithm v0.2 defines a draft algorithmic layer for estimating origin purity and routing uncertain or risky cases toward review.\n\nIt connects:\n\n```text\norigin signals\n↓\nweighted scoring\n↓\nconfidence handling\n↓\nwarning flags\n↓\nseverity levels\n↓\nreview routing\n↓\ndownstream-use guidance\n↓\nplatform UI integration\n↓\nfuture UI control architecture\n```\n\nThe core principle is simple:\n\n```text\nProtect the source layer.\nDetect uncertainty.\nRoute risk to review.\nPreserve creator control.\nDo not automate judgment too early.\n```\n\nIf AI civilization is a river, primary sources are the springs.\n\nThis repository is a draft water-quality inspection model for that river, and a starting point for future creator-controlled origin interfaces.\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsamuraiwriter7%2Fai-purity-detection-algorithm-v0.2","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsamuraiwriter7%2Fai-purity-detection-algorithm-v0.2","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsamuraiwriter7%2Fai-purity-detection-algorithm-v0.2/lists"}