SI Methods: a full experimental-procedures appendix

Replaces the three-paragraph methods sketch with a scientific account of how
the study was run (M1-M7):

- M1 design principles: cheapest falsifying tier; match claim precision to
  instrument precision; every tier gets an oracle independent of the model
  being measured; falsifiers declared before running.
- M2 replication: what a replicate *is* differs by tier (independent lineage /
  lineage incl. fresh init and data order / training seed with test sets held
  fixed), and a table giving every experiment's replicate count with the
  reasoning - why 200 for E4 (per-item binary outcomes), 60 for the bridge
  gate (must detect any departure), 3-5 where the contrast is categorical,
  and 1 for the 7B runs, labelled as single runs.
- M3-M5 per-tier procedures: parameter choices and their justification, the
  correlated-parent construction, why the neural sandbox is synthetic (a
  lossless identity code plus style entropy gives an exact oracle while still
  forcing the model to learn a distribution), MNIST modes and the frozen-CNN
  oracle with its confusion matrix as measurement floor, why no-BatchNorm MLPs
  for the alignment analysis, and for the LLM tier: why Qwen 0.5B/7B (one
  family so scale is the only variable), why procedural tasks rather than a
  benchmark (exact verifier, contamination-free, controlled disjointness, a
  difficulty knob), why LoRA (confines each parent to an additive low-rank
  delta over an identical base, which is what makes weight-space
  recombination well defined), the training algorithm, and the split scheme.
- M6 negative controls, including the one that removed a result: the
  compatible-overlap axis collapsed the delta-cosine predictor from rho=+0.60
  to +0.03.
- M7 statistical procedures.

Also: SI voice converted to first person and terminology synced to the
"biological model" rename; removed a process ghost from the preamble
("Skeleton assembled at Phase 4"); build.py now takes a document argument and
no longer eats documents that lack a title block, so the SI compiles via a new
si.tex wrapper (10 pp). `make paper` builds both PDFs.

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

paper/pnas/build.py

@@ -151,10 +151,12 @@ def figure_env(name: str) -> str:
 
 def convert(text: str) -> str:
     lines = text.split("\n")
+    # Skip the title block only when the document opens with one (main.md separates it with a rule
+    # in the first few lines); si.md has no such block, so nothing is dropped there.
     i = 0
-    while i < len(lines) and lines[i].strip() != "---":
-        i += 1
-    i += 1
+    head = [n for n, ln in enumerate(lines[:10]) if ln.strip() == "---"]
+    if head:
+        i = head[0] + 1
 
     blocks: list[list[str]] = []
     cur: list[str] = []
@@ -214,5 +216,10 @@ def convert(text: str) -> str:
 
 
 if __name__ == "__main__":
-    OUT.write_text(convert(SRC.read_text()))
-    print(f"wrote {OUT}")
+    import sys
+
+    doc = sys.argv[1] if len(sys.argv) > 1 else "main"
+    src = HERE / f"{doc}.md"
+    out = HERE / ("body.tex" if doc == "main" else f"{doc}_body.tex")
+    out.write_text(convert(src.read_text()))
+    print(f"wrote {out}")