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: E2_grounding_phase_boundary
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seed: 20260704
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n_replicates: 100
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generations: 500 # long enough that the g=0 arm slides toward 0 while g>0 arms plateau
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# Headline experiment (blueprint 2.5-E2): sweep the grounding fraction g = m/(n+m);
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# single teacher; proportional grounding (Multinomial(m, p*), the immigration model the
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# exact H_eq of 2.4-3 is derived for); no selection. R=1 so the sweep tracks the closed
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# form. Expect a critical g* << 1 above which stationary H and tail mass stabilise at a
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# positive value tracking H_eq = H* * m(2n+m-1)/(n+2nm+m^2), below which they collapse.
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truth:
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K: 1000
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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: 1.0e-3
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init: truth
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dynamics:
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n: 200
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teachers: {K_T: 1, rho: 0.0, q: 1.0}
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grounding: {m: 0, policy: proportional} # m is overwritten per g by the sweep
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selection: {mode: none, novelty_alpha: 0.0}
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remint: {enabled: false, period: null, H_gate: null}
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metrics:
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kl_floor: 1.0e-9
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support_eps: 1.0e-9
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sweep:
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- param: g
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values: [0.0, 0.005, 0.01, 0.02, 0.05, 0.1, 0.2, 0.4]
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output:
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dir: results/E2
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