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/figS11_directed_recombination/README.md

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+# E10 — directed sex beats biological sex (the distinctly-AI superpower)
+
+**Claim tested.** E9 showed that on rugged (epistatic) landscapes, blind recombination causes
+outbreeding depression — offspring worse than parents. Biology is largely stuck with this: two
+random-mating parents, no way to preview offspring. But an **AI is not** — it can choose mates,
+evaluate many recombinant offspring, and keep only the fittest, over rounds, with no two-parent
+limit. Does this **directed sex** rescue recombination where blind sex fails?
+
+**Setup.** Parents are local optima of a Kauffman NK landscape (`L=12`), swept over ruggedness `K`.
+Three strategies compared, all as deployed capability (fitness ∈ [0,1]): **best single parent**;
+**random sex** (blind mating, free recombination, no offspring selection — biology's default);
+**directed sex** (iterated recombine-then-select-offspring, `rate=0.2`, 5 rounds — the AI move).
+24 replicate landscapes.
+
+### Symbols
+- **random sex** — blind: random parents, free recombination, take the offspring as they come.
+- **directed sex** — choose complementary mates + generate many offspring + keep the fittest + repeat; unbounded parents.
+- **global optimum** — the landscape's best genotype (the ceiling).
+
+### The two panels
+1. **Capability vs ruggedness.** As `K` grows, **random sex (blue) craters** (0.66 → 0.51 — deep
+   outbreeding depression), while **directed sex (red) tracks the best parent and the global optimum**,
+   staying near the ceiling at every ruggedness.
+2. **Edge over the best parent.** Directed sex stays **≥ 0** (at or above the parents) across all `K`;
+   random sex falls to **≈ −0.2** (far below). Directed sex converts a catastrophe into a win.
+
+### Takeaway
+The move biology cannot make — **choose your mates, evaluate your offspring before you commit, and
+recombine as many parents as you like** — is exactly what makes AI sexual reproduction robust. Blind
+merging of entangled models is dangerous; *directed* merging (generate many candidate merges, keep
+the best) is safe and can exceed every parent. This is the practical payoff of the sexual-transmission
+model and the distinctly-AI superpower with no biological analog. **Falsifier (not triggered):** if
+directed sex did no better than random sex, or never recovered the best-parent level on rugged
+landscapes, the "AI beats biology" claim would fail.

results/figS11_directed_recombination/manifest.json

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+{
+  "experiment": "E10",
+  "master_seed": 20260705,
+  "git_commit": "62c68d6c8c4090e62cf9ee17ac7b7d1eff7a6955",
+  "python": "3.14.5",
+  "libraries": {
+    "numpy": "2.5.0",
+    "scipy": "1.18.0",
+    "pandas": "3.0.3",
+    "pyarrow": "24.0.0"
+  },
+  "rows": 120,
+  "results_sha256": "b2d53d0a3949be0b67e3b8dffec56121d54e20c593e6302717a73a8a132f17cb"
+}

results/figS11_directed_recombination/resolved_config.yaml

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+experiment: E10
+seed: 20260705
+n_replicates: 24
+source_config:
+  experiment: E10
+  kind: directed_sex
+  seed: 20260705
+  n_replicates: 24
+  society:
+    L: 12
+    n_parents: 6
+    pop: 200
+    keep: 8
+    rounds: 5
+    rate: 0.2
+  sweep:
+  - param: K
+    values:
+    - 2
+    - 4
+    - 6
+    - 8
+    - 10
+  output:
+    dir: results/figS11_directed_recombination