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

configs/inheritance/figS10_rugged_landscapes.yaml

@@ -0,0 +1,27 @@
+experiment: E9
+kind: recomb_landscape
+seed: 20260705
+n_replicates: 24
+
+# (Landscape robustness / the "why sex?" question — the credibility centerpiece): E8 showed sex wins
+# on an ADDITIVE landscape, where recombination trivially helps. Does it survive EPISTASIS? Parents
+# are local optima ("trained models") of a Kauffman NK landscape whose ruggedness K (epistatic
+# interactions per locus) is swept with the recombination rate. Expect: on smooth/mildly-rugged
+# landscapes recombination helps; on rugged ones FREE recombination (rate~0.5) breaks co-adapted
+# blocks and offspring fall BELOW the parents (outbreeding depression); and the OPTIMAL recombination
+# rate shrinks as ruggedness grows. Design rule: merge freely when skills are complementary/additive;
+# merge sparingly when entangled. Falsifier: recombination rate has no effect, or free recombination
+# never underperforms the parents on rugged landscapes.
+
+society:
+  L: 12
+  n_parents: 6        # trained specialists = local optima of the landscape
+  pop: 200            # recombinant offspring sampled per (K, rate, replicate)
+
+sweep:
+  - param: K
+    values: [0, 2, 4, 6, 8]        # landscape ruggedness (epistasis): 0 = additive, high = rugged
+  - param: rate
+    values: [0.0, 0.05, 0.1, 0.2, 0.35, 0.5]   # clonal -> free recombination
+
+output: {dir: results/figS10_rugged_landscapes}