Rename neural experiments to descriptive paths (drop N* codes)

configs/neural/{N0,N1,N2,N5}.yaml -> {bridge,collapse,grounding,architectures}.yaml,
results dirs likewise. Updated experiment/output.dir fields, comments/docstrings, and
docs; regenerated the four result manifests (now carrying the real git commit). No
functional path resolution referenced the codes (the Makefile globs configs/neural/*.yaml
and tests use inline configs), so nothing breaks. 92 tests green.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

configs/neural/architectures.yaml

@@ -1,9 +1,9 @@
-experiment: N5_architecture_generality
+experiment: architecture_generality
 kind: gen_lineage
 seed: 20260704
 n_replicates: 5
 
-# N5 (a new Layer-1.5 axis, no Layer-1 counterpart): is collapse ARCHITECTURE-GENERAL?
+# (a new Layer-1.5 axis, no Layer-1 counterpart): is collapse ARCHITECTURE-GENERAL?
 # Run the same dry-vs-grounded protocol across three genuinely different learners that
 # share only the generative-collapse operator: the exact histogram (= Wright-Fisher, the
 # analytic anchor), an autoregressive GRU (recurrent), and an autoregressive MLP (feed-
@@ -51,4 +51,4 @@ sweep:
     values: [0.0, 0.05]
 
 output:
-  dir: results/N5
+  dir: results/architectures

configs/neural/bridge.yaml

@@ -1,4 +1,4 @@
-experiment: N0_bridge_histogram
+experiment: bridge_histogram
 kind: gen_lineage
 seed: 20260704
 n_replicates: 60
@@ -39,4 +39,4 @@ sweep:
     values: [0.0, 0.005, 0.01, 0.02, 0.05, 0.1, 0.2, 0.4]
 
 output:
-  dir: results/N0
+  dir: results/bridge

configs/neural/collapse.yaml

@@ -1,9 +1,9 @@
-experiment: N1_collapse_in_weights
+experiment: collapse_in_weights
 kind: gen_lineage
 seed: 20260704
 n_replicates: 5
 
-# N1 (Layer 1.5, maps to Layer-1 E1 / blueprint C1): does model collapse appear in REAL
+# (maps to Layer-1 E1 / blueprint C1): does model collapse appear in REAL
 # trained weights under dry recursive self-training, and does a little grounding arrest it?
 # An autoregressive RNN is retrained each generation on n samples drawn from the previous
 # generation's RNN (drift), optionally mixed with m verifier-grounded samples. Expect: the
@@ -47,4 +47,4 @@ sweep:
     values: [0.0, 0.02, 0.05, 0.1]
 
 output:
-  dir: results/N1
+  dir: results/collapse

configs/neural/grounding.yaml

@@ -1,9 +1,9 @@
-experiment: N2_grounding_phase_boundary_neural
+experiment: grounding_phase_boundary
 kind: gen_lineage
 seed: 20260704
 n_replicates: 5
 
-# N2 (Layer 1.5 headline, maps to Layer-1 E2): the grounding phase boundary in REAL weights.
+# (Layer 1.5 headline, maps to Layer-1 E2): the grounding phase boundary in REAL weights.
 # Sweep the grounding fraction g = m/(n+m) and locate the neural critical g* at which
 # stationary diversity is restored. Layer 1 found g* = 0.048 << 1. The neural regime (finite
 # model capacity, a smaller K so gen-0 fidelity holds) will not reproduce that value exactly
@@ -47,4 +47,4 @@ sweep:
     values: [0.0, 0.005, 0.01, 0.02, 0.05, 0.1, 0.2]
 
 output:
-  dir: results/N2
+  dir: results/grounding