Restructure: descriptive tier and experiment names, paper/manuscript
- paper/pnas -> paper/manuscript (venue-neutral)
- configs/layer1 -> configs/inheritance, src/knowledge -> src/inheritance
(imported as `inheritance`), make layer1 -> make inheritance; layer2 alias dropped
- inheritance and trained-network bundles named after the manuscript figure
they feed (fig2_grounding_sweep, figS3_rebaselining, ...), or descriptively
where they feed none; configs keep their `experiment:` value so parquet
hashes are unchanged, only output.dir moves
- figure scripts, SI figure sources, notebooks, REPRODUCING.md, README and the
SI Methods/tables updated; make clean no longer deletes tracked manifests;
reproduce.sh hashes the s{seed}/ layouts too
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Y64o8FKP7rCuXzC48pxpMm
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experiment: E4_multiteacher_decorrelation
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kind: coverage
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seed: 20260704
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n_replicates: 200
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# Multi-teacher recombination (blueprint 2.5-E4 / 2.7.1). Build K_T teachers with exact
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# marginal retention q and pairwise retention-correlation rho, form the pupil from their
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# mixture (n draws total = matched budget), and report TWO coverages:
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# union_coverage -> construction-level U(K_T,rho,q) (must match the closed form)
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# surviving_coverage-> tail items that survive the pupil's size-n resampling (+ grounding)
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# Expect: both rise with K_T and (1-rho); at rho=1 many teachers give no benefit over one;
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# the union-surviving gap shrinks as grounding g rises.
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truth:
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K: 500
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R: 1
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tail: zipf
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zipf_s: 1.1
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tail_frac: 0.5
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tail_threshold: 2.0e-3
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coverage:
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n: 300 # pupil sample size (matched budget across teachers)
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q: 0.5 # per-teacher marginal tail retention
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sweep:
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- param: K_T
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values: [1, 2, 3, 5]
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- param: rho
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values: [0.0, 0.25, 0.5, 0.75, 1.0]
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- param: g
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values: [0.0, 0.02, 0.05]
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output:
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dir: results/E4
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