giorgio/MachineSex
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions

Fig. 1 revision: pop-gen definitions as row labels, title into the caption, solid header row

Browse source 
Row labels now teach the vocabulary (grounding = immigration, recombination =
sex, epistasis, the composed society, speciation = reproductive isolation),
each with a two-to-three-line definition in the left margin, replacing the
question taglines. The in-figure title/arrow is removed (the caption carries
it); the tier header row is now solid-colour with white text so the
model-nature band reads as a header rather than a content row.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01BkRLcc18rwT2Lysu6PbG7v
This commit is contained in:
Giorgio Gilestro 2026-09-07 11:21:06 +01:00
parent 0159e2839a
commit e42fe497ff
5 changed files with 39 additions and 36 deletions
Download patch file Download diff file Expand all files Collapse all files

2
paper/pnas/body.tex
View file

@ -20,7 +20,7 @@ An operator of a model population faces recurring decisions for which there is n
\begin{figure*}[p]\centering % fig1
\includegraphics[width=\textwidth]{figs/fig1.pdf}
\caption{The experimental programme. Each population-genetic abstraction (Table 1) is tested at up to three tiers of model architecture, ordered left to right by increasing realism: an exact Wright--Fisher simulator over knowledge distributions (closed forms; bitwise-reproducible), trained neural networks measured against exact oracles (recurrent, feedforward, and variational-autoencoder generators on a synthetic mode universe, and a convolutional VAE on MNIST), and language models (LoRA specialists on Qwen bases at 0.5B and 7B, scored by an exact-match verifier). Rows are the paper's five questions; filled cells name the experiments run at each tier; dashed cells were not tested, and the composed society at language-model scale is the paper's stated gap.}\label{fig1}
\caption{The experimental programme. Each population-genetic abstraction (Table 1) is tested at up to three tiers of model architecture, ordered left to right by increasing realism: an exact Wright--Fisher simulator over knowledge distributions (closed forms; bitwise-reproducible), trained neural networks measured against exact oracles (recurrent, feedforward, and variational-autoencoder generators on a synthetic mode universe, and a convolutional VAE on MNIST), and language models (LoRA specialists on Qwen bases at 0.5B and 7B, scored by an exact-match verifier). The same population-genetic abstractions are carried across the three tiers. Rows are the framework's mechanisms, each defined at the left margin; filled cells name the experiments run at each tier; dashed cells were not tested, and the composed society at language-model scale is the paper's stated gap.}\label{fig1}
\end{figure*}
\section*{The minimal model, and where its exactness ends}