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academy/evren: curriculum v0.2 — adaptive selection, retention, diagn… - #21
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…osis - selection.py: LearningProgressSelector (pooled family signatures, |Δ success| learning progress, per-atom-class weakness targeting, novelty recovery; deterministic, checkpointable) - diversity.py: Jaccard/entropy/coverage/novelty metrics - retention.py: frozen-substrate repeated-probe protocol (per-config) - diagnosis.py: root-causes the v0.1 null result (eval artifact: one-config-per-seed draws; plus trained-state memory saturation) - curriculum_experiment.py: matched-budget 5-condition comparison (uniform/ascending/calibrated/proc_lp/teacher_lp), per-config eval grids, paired bootstrap CIs, zero API calls, state persistence - CLI: evren-curriculum, evren-diagnose (warn on hash randomization) - configs/academy_v01.toml: [evren.curriculum] section - tests: +5 suites (selection/diversity/retention/diagnosis/experiment) - docs/EVREN_CURRICULUM_V02.md: protocol + measured results - pinned run (PYTHONHASHSEED=0): LP and teacher-source effects exactly +0.0000 on classic transfer; ascending only non-uniform (+0.042); retention flat. Honest negative result: student memory saturation is the binding constraint, not curriculum source.
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