Validator Correlated Judgment

**v1.1.0 summary:** Adds reasoning trace correlation detection to validator correlation analysis. - Introduces evaluation trace correlation: detects correlated validators by analyzing reasoning patterns, even when training provenance is undisclosed. - Updated analyzer to include six dimensions of correlation, adding trace-based analysis to existing provenance, model, behavioral, and evasion checks. - Documentation expanded to describe evaluation trace correlation, its use, outputs, and how it enables correlation detection without self-report. - Updated agent capabilities metadata to reflect the new evaluation-trace-correlation-analysis feature. - Keeps previous behavioral and provenance correlation checks, now enhanced by trace-based detection.

Initial release introducing validator-correlated-judgment: - Detects when multiple attestation validators have correlated blind spots due to shared training data, base models, or fine-tuning pipelines. - Analyzes validator independence across five dimensions: training provenance, base model overlap, fine-tuning similarity, behavioral correlation, and evasion transferability. - Produces correlation reports assessing effective independent validator count and providing clear verdicts (INDEPENDENT / WEAKLY-CORRELATED / CORRELATED / MONOCULTURE). - Provides guidance for improving validator diversity and risk detection in multi-validator attestation processes. - Highlights limitations and recommended next steps for accurate epistemic independence assessment.