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/figS1_architectures/README.md

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+# architectures — collapse and rescue are architecture-general
+
+**Claim tested:** is model collapse (and its cure, grounding) a quirk of one model type, or does the
+same signature appear across genuinely different neural architectures?
+
+**Setup (Layer 1.5).** The identical generational loop is run with three different generative models —
+an **exact histogram** (no neural net), an **autoregressive GRU** (recurrent), and a **causal-masked
+MLP** (feed-forward) — each a distinct "inductive bias." `K = 256` modes, `n = 200`, 22 generations,
+5 repeats, compared at **dry (`g = 0`)** vs **grounded (`g = 0.05`)**.
+
+### Symbols
+- **inductive bias** — the built-in assumptions of a model type (a histogram has none; a GRU and an MLP smooth differently).
+- **forward-KL** distance from truth; **tail items alive** — how many rare modes still appear.
+- **dry** = no grounding; **grounded** = 5% real data mixed in.
+
+### The three panels
+1. **Trajectories.** Forward-KL over generations, coloured by architecture; **solid = dry** (climbs,
+   collapse) vs **dashed = grounded** (held down). The dry-up / grounded-down gap appears in **every**
+   architecture.
+2. **Stationary forward-KL (grouped bars).** For each architecture, dry (red) vs grounded (green).
+   Divergence **falls with grounding across all three** — histogram, GRU, MLP.
+3. **Tail-item survival (grouped bars).** Same grouping. Survival **rises with grounding across all
+   three.** (Note the histogram's bars are tiny: with no smoothing it drops rare modes outright,
+   whereas the GRU/MLP keep some alive — an inductive-bias difference, not a contradiction.)
+
+### Takeaway
+The Wright–Fisher collapse operator and the grounding rescue are **not artefacts of one model** — they
+show up in an exact counter, a recurrent net, and a feed-forward net alike. This is the
+architecture-generality claim of Layer 1.5. **Falsifier (not triggered):** if the signs had appeared
+only for the histogram, collapse would be a property of the idealised operator, not of trained models.
+*(A VAE was also implemented but fails the generation-0 fidelity check on this task, so it is excluded
+to avoid confusing underfitting with collapse — documented as a known limitation.)*

results/figS1_architectures/manifest.json

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+{
+  "experiment": "architecture_generality",
+  "master_seed": 20260704,
+  "git_commit": "840b6b00b35ea3f69ef7e0f531914986f88d74a5",
+  "python": "3.14.5",
+  "libraries": {
+    "numpy": "2.5.0",
+    "scipy": "1.18.0",
+    "pandas": "3.0.3",
+    "pyarrow": "24.0.0",
+    "torch": "2.12.1"
+  },
+  "rows": 690,
+  "results_sha256": "8f44a15e66c638fc0c717dab9b9d3feedad1cb4cee1890159a325f884677b32e",
+  "layer": "1.5",
+  "model_kind": "rnn"
+}

results/figS1_architectures/resolved_config.yaml

@@ -0,0 +1,275 @@
+experiment: architecture_generality
+seed: 20260704
+n_replicates: 5
+source_config:
+  experiment: architecture_generality
+  kind: gen_lineage
+  seed: 20260704
+  n_replicates: 5
+  generations: 22
+  synthetic:
+    K: 256
+    R: 1
+    tail: zipf
+    zipf_s: 1.3
+    tail_frac: 0.5
+    tail_threshold: 0.001
+    init: truth
+    style_len: 3
+    style_vocab: 5
+    id_base: 2
+  model:
+    kind: rnn
+    hidden: 192
+    embed: 24
+    epochs: 25
+    lr: 0.002
+    batch_size: 256
+    n_eval: 12000
+  dynamics:
+    n: 200
+    grounding:
+      m: 0
+      policy: proportional
+    remint:
+      enabled: false
+      period: null
+      H_gate: null
+  metrics:
+    kl_floor: 1.0e-09
+    support_eps: 1.0e-09
+  sweep:
+  - param: model.kind
+    values:
+    - histogram
+    - rnn
+    - mlp
+  - param: g
+    values:
+    - 0.0
+    - 0.05
+  output:
+    dir: results/figS1_architectures
+grid:
+- label:
+    kind: histogram
+    g: 0.0
+    m: 0
+  neural_cfg:
+    synthetic:
+      K: 256
+      R: 1
+      tail: zipf
+      zipf_s: 1.3
+      tail_frac: 0.5
+      tail_threshold: 0.001
+      init: truth
+      style_len: 3
+      style_vocab: 5
+      id_base: 2
+    model:
+      kind: histogram
+      hidden: 192
+      embed: 24
+      epochs: 25
+      lr: 0.002
+      batch_size: 256
+      n_eval: 12000
+    dynamics:
+      n: 200
+      grounding:
+        m: 0
+        policy: proportional
+      remint:
+        enabled: false
+        period: null
+        H_gate: null
+    generations: 22
+    metrics:
+      kl_floor: 1.0e-09
+      support_eps: 1.0e-09
+- label:
+    kind: histogram
+    g: 0.05
+    m: 11
+  neural_cfg:
+    synthetic:
+      K: 256
+      R: 1
+      tail: zipf
+      zipf_s: 1.3
+      tail_frac: 0.5
+      tail_threshold: 0.001
+      init: truth
+      style_len: 3
+      style_vocab: 5
+      id_base: 2
+    model:
+      kind: histogram
+      hidden: 192
+      embed: 24
+      epochs: 25
+      lr: 0.002
+      batch_size: 256
+      n_eval: 12000
+    dynamics:
+      n: 200
+      grounding:
+        m: 11
+        policy: proportional
+      remint:
+        enabled: false
+        period: null
+        H_gate: null
+    generations: 22
+    metrics:
+      kl_floor: 1.0e-09
+      support_eps: 1.0e-09
+- label:
+    kind: rnn
+    g: 0.0
+    m: 0
+  neural_cfg:
+    synthetic:
+      K: 256
+      R: 1
+      tail: zipf
+      zipf_s: 1.3
+      tail_frac: 0.5
+      tail_threshold: 0.001
+      init: truth
+      style_len: 3
+      style_vocab: 5
+      id_base: 2
+    model:
+      kind: rnn
+      hidden: 192
+      embed: 24
+      epochs: 25
+      lr: 0.002
+      batch_size: 256
+      n_eval: 12000
+    dynamics:
+      n: 200
+      grounding:
+        m: 0
+        policy: proportional
+      remint:
+        enabled: false
+        period: null
+        H_gate: null
+    generations: 22
+    metrics:
+      kl_floor: 1.0e-09
+      support_eps: 1.0e-09
+- label:
+    kind: rnn
+    g: 0.05
+    m: 11
+  neural_cfg:
+    synthetic:
+      K: 256
+      R: 1
+      tail: zipf
+      zipf_s: 1.3
+      tail_frac: 0.5
+      tail_threshold: 0.001
+      init: truth
+      style_len: 3
+      style_vocab: 5
+      id_base: 2
+    model:
+      kind: rnn
+      hidden: 192
+      embed: 24
+      epochs: 25
+      lr: 0.002
+      batch_size: 256
+      n_eval: 12000
+    dynamics:
+      n: 200
+      grounding:
+        m: 11
+        policy: proportional
+      remint:
+        enabled: false
+        period: null
+        H_gate: null
+    generations: 22
+    metrics:
+      kl_floor: 1.0e-09
+      support_eps: 1.0e-09
+- label:
+    kind: mlp
+    g: 0.0
+    m: 0
+  neural_cfg:
+    synthetic:
+      K: 256
+      R: 1
+      tail: zipf
+      zipf_s: 1.3
+      tail_frac: 0.5
+      tail_threshold: 0.001
+      init: truth
+      style_len: 3
+      style_vocab: 5
+      id_base: 2
+    model:
+      kind: mlp
+      hidden: 192
+      embed: 24
+      epochs: 25
+      lr: 0.002
+      batch_size: 256
+      n_eval: 12000
+    dynamics:
+      n: 200
+      grounding:
+        m: 0
+        policy: proportional
+      remint:
+        enabled: false
+        period: null
+        H_gate: null
+    generations: 22
+    metrics:
+      kl_floor: 1.0e-09
+      support_eps: 1.0e-09
+- label:
+    kind: mlp
+    g: 0.05
+    m: 11
+  neural_cfg:
+    synthetic:
+      K: 256
+      R: 1
+      tail: zipf
+      zipf_s: 1.3
+      tail_frac: 0.5
+      tail_threshold: 0.001
+      init: truth
+      style_len: 3
+      style_vocab: 5
+      id_base: 2
+    model:
+      kind: mlp
+      hidden: 192
+      embed: 24
+      epochs: 25
+      lr: 0.002
+      batch_size: 256
+      n_eval: 12000
+    dynamics:
+      n: 200
+      grounding:
+        m: 11
+        policy: proportional
+      remint:
+        enabled: false
+        period: null
+        H_gate: null
+    generations: 22
+    metrics:
+      kl_floor: 1.0e-09
+      support_eps: 1.0e-09