E13b/c: harden real-weight speciation — full symmetry group + emergent-divergence null

E13c (the symmetry defense): alignment now runs modulo the FULL
function-preserving unit symmetry group of a ReLU MLP (per-unit positive
rescaling via canonicalise_scale, composed with Re-Basin permutations;
sanity gate recovers a permuted-and-rescaled copy exactly). Verdict: the
full group removes the independent-init barrier (residual 0.001) and
essentially none of the conflict barrier (0.502 -> 0.497) — the residual
is functional, not a missed symmetry (answers arXiv:2606.23607). The
cliff gains a hybrid-fitness readout: merged accuracy 0.97 -> 0.03 with
conflict. Floor proposition drafted (paper/si-notes.md S1): endpoint
invariance + max(eps_A, eps_B) >= mu(S)/2 for any merged model under any
alignment group.

E13b (emergent divergence): pre-registered second reading — with NO
conflicting training signal (disjoint class specialists; rolled-input
conventions), residual is 0.000 at every divergence to t_div=3200, and
the merge RESCUES the forgetting specialists (parents 0.535/0.474 ->
merged 0.955; a sustained Fisher-Muller rescue at zero barrier).
Speciation in real weights requires functional conflict; it does not
emerge from compatible specialisation on shared ancestry. LLM-scale
over-specialisation (cf. 2607.11997) deferred to Phase-3 llm_speciation.

3-panel figure, READMEs, +2 tests (149 green), make mnist wired.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01BkRLcc18rwT2Lysu6PbG7v

configs/neural/speciation_real_emergent.yaml

@@ -0,0 +1,36 @@
+experiment: speciation_real_emergent
+kind: speciation_real
+seed: 813
+n_replicates: 4
+
+# E13b — EMERGENT model speciation (the decisive experiment; PNAS work order Phase 1). The committed
+# E13 cliff IMPOSES contradiction (conflicting label maps); a true Bateson-Dobzhansky-Muller
+# incompatibility is emergent — each lineage's changes harmless alone, incompatible only in
+# combination. Here the two children diverge WITHOUT any imposed conflict:
+#   shared   — control anchor (same task, same data): residual should stay ~0 at every divergence.
+#   disjoint — A trains only on classes 0-4, B only on 5-9 (complementary specialists, no
+#              contradiction). The money curve is acc_merge_* vs t_div against the parents: at low
+#              divergence the merge should RESCUE the two forgetting specialists (Fisher-Muller);
+#              if a residual barrier emerges and merged accuracy then falls with divergence, that is
+#              E12's compatible -> outbreeding-depression -> inviability trajectory, emergent in real
+#              weights. If the residual stays ~0, the honest conclusion is that models are SAFER to
+#              merge than the biological analogy predicts (a bound on the analogy) - either outcome
+#              is reportable; pre-registered falsifier language, do not tune toward one.
+#   augment  — same task/labels, A on +3px-rolled images, B on -3px-rolled (pure representational
+#              conventions, zero output conflict): does convention drift alone isolate?
+# Alignment is reported permutation-only (residual) AND scale-canonicalised+permutation
+# (residual_scale, the full ReLU unit symmetry group; E13c) so any emergent residual cannot be
+# dismissed as a missed symmetry (cf. arXiv:2606.23607).
+
+speciation_real:
+  sizes: [784, 512, 512, 10]
+  conditions: [shared, disjoint, augment]
+  t_div: [100, 200, 400, 800, 1600, 3200]
+  base_steps: 500
+  lr: 0.05
+  batch: 128
+  n_eval: 2000
+  data_root: data
+
+output:
+  dir: results/speciation_real_emergent