Update CHANGELOG.md

Author: SamuraiWriter7

CHANGELOG.md

@@ -8,110 +8,128 @@ This project follows a draft-oriented versioning model while the specification r
 
 ## [Unreleased]
 
-### Planned
-
-- Add additional v0.2 examples for:
-  - high-confidence natural-source assessment
-  - hybrid structural-originality assessment
-  - disputed-origin assessment
-  - declaration-conflict assessment
-- Add a dedicated review-routing model document.
-- Add relationship documents for:
-  - CollapseMonitor
-  - Royalty Readiness
-  - Trace Protocol
-  - Structure Fingerprint
-- Extend the schema to support:
-  - detailed scoring model output
-  - warning-flag detail objects
-  - recursive synthetic risk output
-  - review-routing metadata
-
-### Notes
+### Added
 
-The next stage should focus on making the v0.2 model more operational without turning purity scoring into automatic legal or financial judgment.
+- Added `docs/relationship-to-consciousness-circle.md` to explain how AI Purity Detection relates to meaning-origin assessment, initial friction, resonance patterns, and Consciousness Circle.
+- Added `docs/relationship-to-royalty-readiness.md` to explain how purity assessment supports royalty-readiness review without directly determining allocation or payment.
+- Added `docs/relationship-to-collapse-monitor.md` to explain how source-level purity assessments may provide aggregate signals for CollapseMonitor and ecosystem-health monitoring.
+- Added `docs/api-design-notes.md` to outline possible API endpoints, core objects, response structures, safety rules, and integration paths for future implementation.
 
----
+### Changed
 
-## [0.2.0] - 2026-05-25
+- Expanded the v0.2 relationship layer beyond scoring and warning flags.
+- Clarified that AI Purity Detection can connect to:
+  - Consciousness Circle
+  - Royalty Readiness
+  - CollapseMonitor
+  - Trace Protocol
+  - future API-based source-preservation systems
+- Strengthened the distinction between:
+  - assessment and judgment
+  - purity scoring and royalty allocation
+  - source integrity and meaning integrity
+  - local source assessment and ecosystem-level monitoring
 
-### Added
+### Notes
 
-- Added initial `README.md` for **AI Purity Detection Algorithm v0.2**.
-- Added `docs/v0.2-roadmap.md` to define the proposed direction for the v0.2 specification.
-- Added `docs/scoring-weighting-model.md` to define a draft signal-weighting and confidence-adjusted scoring model.
-- Added `docs/warning-flag-severity-model.md` to define warning-flag severity levels, review routing, and downstream impact handling.
-- Added `schemas/purity-assessment.schema.json` for validating purity assessment examples.
-- Added `examples/purity-assessment.sample.yaml` as a standard purity assessment example.
-- Added `examples/purity-assessment.low-confidence.sample.yaml` to demonstrate weak provenance, unclear origin, low confidence, review-required routing, and blocked royalty-readiness status.
-- Added `examples/purity-assessment.recursive-synthetic-risk.sample.yaml` to demonstrate high recursive synthetic risk, weak primary-source provenance, high AI-pattern similarity, blocked training use, and blocked royalty-readiness status.
-- Added `.github/workflows/validate-examples.yml` to validate YAML examples against the JSON Schema.
-- Added `LICENSE`.
-
-### Defined
-
-- Defined `origin_purity_score` as a normalized estimate of source-origin composition.
-- Defined `ai_generated_ratio` as a separate estimate of AI-generated or AI-assisted content ratio.
-- Defined `warning_flags` as routing and review-support signals.
-- Defined a draft signal-weighting model using:
-  - `provenance_evidence_score`
-  - `author_declaration_score`
-  - `structural_originality_score`
-  - `revision_lineage_score`
-  - `citation_transparency_score`
-  - `ai_pattern_risk_score`
-  - `structure_fingerprint_distinctiveness_score`
-  - `recursive_synthetic_risk_score`
-  - `signal_confidence_quality_score`
-- Defined warning severity levels:
-  - `info`
-  - `warning`
-  - `review_required`
-  - `blocking`
-- Defined review-routing modes:
-  - `none`
-  - `recommended`
-  - `required`
-  - `blocking_review`
-
-### Validation
-
-- Added GitHub Actions validation for:
-  - `examples/purity-assessment.sample.yaml`
-  - `examples/purity-assessment.low-confidence.sample.yaml`
-  - `examples/purity-assessment.recursive-synthetic-risk.sample.yaml`
-- Confirmed that all three example files pass validation against:
-  - `schemas/purity-assessment.schema.json`
+The current `Unreleased` layer prepares the specification for broader integration.
 
-### Notes
+The newly added relationship documents position AI Purity Detection Algorithm v0.2 as a bridge between:
 
-This release establishes **AI Purity Detection Algorithm v0.2** as a draft algorithmic layer for source-preservation systems.
+```text
+source-origin assessment
+↓
+meaning-structure assessment
+↓
+collapse-risk monitoring
+↓
+royalty-readiness review
+↓
+future API implementation
+
+These documents do not turn purity scoring into an automatic legal, financial, or metaphysical decision system.
+
+They preserve the core principle:
+
+Expose evidence.
+Expose uncertainty.
+Route risk to review.
+Do not automate judgment too early.
+[0.2.0] - 2026-05-25
+Added
+Added initial README.md for AI Purity Detection Algorithm v0.2.
+Added docs/v0.2-roadmap.md to define the proposed direction for the v0.2 specification.
+Added docs/scoring-weighting-model.md to define a draft signal-weighting and confidence-adjusted scoring model.
+Added docs/warning-flag-severity-model.md to define warning-flag severity levels, review routing, and downstream impact handling.
+Added schemas/purity-assessment.schema.json for validating purity assessment examples.
+Added examples/purity-assessment.sample.yaml as a standard purity assessment example.
+Added examples/purity-assessment.low-confidence.sample.yaml to demonstrate weak provenance, unclear origin, low confidence, review-required routing, and blocked royalty-readiness status.
+Added examples/purity-assessment.recursive-synthetic-risk.sample.yaml to demonstrate high recursive synthetic risk, weak primary-source provenance, high AI-pattern similarity, blocked training use, and blocked royalty-readiness status.
+Added .github/workflows/validate-examples.yml to validate YAML examples against the JSON Schema.
+Added LICENSE.
+Added CITATION.cff.
+Defined
+Defined origin_purity_score as a normalized estimate of source-origin composition.
+Defined ai_generated_ratio as a separate estimate of AI-generated or AI-assisted content ratio.
+Defined warning_flags as routing and review-support signals.
+Defined recursive_synthetic_risk as a key warning and ecosystem-risk signal.
+Defined a draft signal-weighting model using:
+provenance_evidence_score
+author_declaration_score
+structural_originality_score
+revision_lineage_score
+citation_transparency_score
+ai_pattern_risk_score
+structure_fingerprint_distinctiveness_score
+recursive_synthetic_risk_score
+signal_confidence_quality_score
+Defined warning severity levels:
+info
+warning
+review_required
+blocking
+Defined review-routing modes:
+none
+recommended
+required
+blocking_review
+Validation
+Added GitHub Actions validation for:
+examples/purity-assessment.sample.yaml
+examples/purity-assessment.low-confidence.sample.yaml
+examples/purity-assessment.recursive-synthetic-risk.sample.yaml
+Confirmed that all three example files pass validation against:
+schemas/purity-assessment.schema.json
+Notes
+
+This release establishes AI Purity Detection Algorithm v0.2 as a draft algorithmic layer for source-preservation systems.
 
 The specification focuses on:
 
-- origin-purity scoring
-- natural / synthetic data separation
-- hybrid data classification
-- recursive synthetic risk detection
-- warning-flag severity
-- confidence handling
-- review routing
-- downstream-use guidance
-- model-collapse monitoring support
-- royalty-readiness review support
+origin-purity scoring
+natural / synthetic data separation
+hybrid data classification
+recursive synthetic risk detection
+warning-flag severity
+confidence handling
+review routing
+downstream-use guidance
+model-collapse monitoring support
+royalty-readiness review support
 
 This release does not attempt to:
 
-- prove legal authorship
-- determine copyright ownership
-- automatically assign royalties
-- ban AI-assisted creation
-- punish synthetic content
-- perfectly detect AI-generated text
-- replace human or multi-wing review
+prove legal authorship
+determine copyright ownership
+automatically assign royalties
+ban AI-assisted creation
+punish synthetic content
+perfectly detect AI-generated text
+replace human or multi-wing review
 
 The core principle remains:
 
-```text
 Purity is not moral judgment.
 Purity is ecological signal.
+
+This version provides a review-support and ecosystem-health layer for future AI source-preservation systems.