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

results/collapse_null/README.md

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+# E1 — Distillation without grounding collapses, tail-first
+
+**Claim tested:** if a model is trained only on the previous model's output, generation after
+generation, does it lose knowledge — and does the *rare* knowledge go first?
+
+**Setup (Layer 1, pure math).** A "population" of `K = 500` items with a fixed true frequency
+`p*` shaped like a Zipf curve (a few common items, a long tail of rare ones). Each generation we
+draw `n = 100` samples from the current model and refit — **no real data is ever added** (`g = 0`).
+Run for 600 generations, averaged over 100 independent repeats.
+
+### Symbols
+- **`p*`** — the true frequencies (fixed reality). **`p_t`** — the model's frequencies at generation *t* (drifts).
+- **`H`** heterozygosity = diversity (1 = everything equally likely, 0 = one item left). **`H*`** = diversity of the truth.
+- **forward-KL** `D(p*‖p_t)` — how far the model has drifted from truth (0 = perfect, grows without bound as the tail is forgotten).
+- **support** = how many items still have any probability. **head/tail** = common/rare items.
+
+### The three panels
+1. **Geometric decay.** Blue = the simulated diversity `H`; black dashed = the exact textbook law
+   `H₀·(1 − 1/n)^t`. They sit on top of each other — the loss of diversity is *exactly* the
+   population-genetics drift law, not an approximation. (This is the validation gate: if these two
+   curves disagreed, the simulator would be wrong.)
+2. **Tail dies first** (log axis). Red = fraction of *rare* (tail) items still alive; green =
+   fraction of *common* (head) items still alive. The red curve plunges far faster — rare knowledge
+   is lost roughly an order of magnitude sooner than common knowledge.
+3. **Collapse.** Purple (left axis, log) = number of distinct items surviving, falling from 500
+   toward ~1 (everything collapses onto a single dominant item). Orange (right axis) = forward-KL to
+   truth, diverging as the tail vanishes.
+
+### Takeaway
+Unchecked model-on-model training is a ratchet: diversity decays on a precise mathematical schedule,
+and the rare tail is destroyed first. **Falsifier (not triggered):** if `H` had stayed flat, the
+whole thesis would fail. It didn't.

results/collapse_null/manifest.json

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+{
+  "experiment": "E1_reproduce_collapse",
+  "master_seed": 20260704,
+  "git_commit": "a6eb9b75124779375fa1a0b3a64115ecd705b218",
+  "python": "3.14.5",
+  "libraries": {
+    "numpy": "2.5.0",
+    "scipy": "1.18.0",
+    "pandas": "3.0.3",
+    "pyarrow": "24.0.0"
+  },
+  "rows": 60100,
+  "results_sha256": "038bf62046d593a61d0177f988f76897c9af5d9c370dc4d19bf37dc68d47afde"
+}

results/collapse_null/resolved_config.yaml

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+experiment: E1_reproduce_collapse
+seed: 20260704
+n_replicates: 100
+source_config:
+  experiment: E1_reproduce_collapse
+  seed: 20260704
+  n_replicates: 100
+  generations: 600
+  truth:
+    K: 500
+    R: 1
+    tail: zipf
+    zipf_s: 1.1
+    tail_frac: 0.5
+    tail_threshold: 0.001
+    init: truth
+  dynamics:
+    n: 100
+    teachers:
+      K_T: 1
+      rho: 0.0
+      q: 1.0
+    grounding:
+      m: 0
+      policy: proportional
+    selection:
+      mode: none
+      novelty_alpha: 0.0
+    remint:
+      enabled: false
+      period: null
+      H_gate: null
+  metrics:
+    kl_floor: 1.0e-09
+    support_eps: 1.0e-09
+  output:
+    dir: results/collapse_null
+grid:
+- label: {}
+  lineage_cfg:
+    truth:
+      K: 500
+      R: 1
+      tail: zipf
+      zipf_s: 1.1
+      tail_frac: 0.5
+      tail_threshold: 0.001
+      init: truth
+    dynamics:
+      n: 100
+      teachers:
+        K_T: 1
+        rho: 0.0
+        q: 1.0
+      grounding:
+        m: 0
+        policy: proportional
+      selection:
+        mode: none
+        novelty_alpha: 0.0
+      remint:
+        enabled: false
+        period: null
+        H_gate: null
+    generations: 600
+    metrics:
+      kl_floor: 1.0e-09
+      support_eps: 1.0e-09