Cognitive Nutrition for Foundation Models: Empirical Validation of the PEST Framework through a Provenance-Embedded Data Refinery
Cognitive Nutrition for Foundation Models: Empirical Validation of the PEST Framework through a Provenance-Embedded Data Refinery
v2.0 (2026-03-02): Aligned all cross-referenced metrics from The Density Imperative (now under DMLR peer review, Submission #186): CogBench cognitive swing corrected from 63-point to 24.1-point, CogBench scores corrected to 0.174/0.415/0.378, reduction corrected from 54.4% to 54.0%, semantic coverage corrected from 160% to 159.6% throughout.
Architecture of a provenance-embedded data refinery that produces semantically dense training data. Validates the PEST framework through controlled ablation showing a 24.1-point CogBench cognitive swing between sparse and dense fine-tuning conditions.
data refinery, metadata enrichment, provenance, semantic density, data stewardship, GLAM, perceptual hashing
data refinery, metadata enrichment, provenance, semantic density, data stewardship, GLAM, perceptual hashing
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