Giorgio Gilestro
a88289964a
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
28 lines
966 B
TeX
28 lines
966 B
TeX
% SI Appendix — readable single-column build (tectonic/XeLaTeX). Content is generated from si.md
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% by `python paper/pnas/build.py si`; the pnas.cls reflow happens at submission.
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\ifdefined\XeTeXversion\else\ifdefined\pdfoutput\pdfoutput=1\fi\fi
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\documentclass[11pt]{article}
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\usepackage[a4paper, margin=1.0in]{geometry}
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\usepackage{graphicx}
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\usepackage{amsmath, amssymb}
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\usepackage[hidelinks]{hyperref}
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\usepackage{microtype}
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\setlength{\parskip}{0.35em}
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\renewcommand{\thesection}{S\arabic{section}}
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\title{\textbf{Supporting Information}\\[0.5em]
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\large The evolution of sex for artificial intelligence:\\
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a population-genetic framework for multigenerational model populations}
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\author{Giorgio F.\ Gilestro\\[0.2em]
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\normalsize Department of Life Sciences, Imperial College London\\
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\normalsize \href{mailto:giorgio@gilest.ro}{giorgio@gilest.ro}}
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\date{Generated from \texttt{paper/pnas/si.md}}
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\begin{document}
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\maketitle
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\input{si_body}
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\end{document}
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