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| author | haoyuren <13851610112@163.com> | 2026-07-28 21:17:38 +0800 |
|---|---|---|
| committer | haoyuren <13851610112@163.com> | 2026-07-28 21:17:38 +0800 |
| commit | 3b5f01cb4db9efc4ceb2ba17709bbfc82a63e660 (patch) | |
| tree | ad4e2321373fc9e551ffeb2ca27f5533ca9e9bdb /outputs/tables/cnn_initialization_rows.tex | |
| parent | 18bf25f34f6d352605086aa8fe63977baacc315b (diff) | |
Add appendix table generator and generated LaTeX fragments
generate_paper_tables.py reads the row-level CSVs and emits the four
appendix tables (initialization calibration rows, finite-time cells,
CNN calibration rows, learning-rate regimes) with the paper's nested
uncertainty convention. The fragments are included by the manuscript
via \input; no table value is transcribed manually.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Diffstat (limited to 'outputs/tables/cnn_initialization_rows.tex')
| -rw-r--r-- | outputs/tables/cnn_initialization_rows.tex | 14 |
1 files changed, 14 insertions, 0 deletions
diff --git a/outputs/tables/cnn_initialization_rows.tex b/outputs/tables/cnn_initialization_rows.tex new file mode 100644 index 0000000..9066ce0 --- /dev/null +++ b/outputs/tables/cnn_initialization_rows.tex @@ -0,0 +1,14 @@ +\begin{tabular}{@{}lrccc@{}} +\toprule +Rule & Init & Prediction & Measured & SE \\ +\midrule +DFA & 0 & 0.647613 & 0.652511 & 0.0051 \\ +DFA & 1 & 0.591587 & 0.587769 & 0.0066 \\ +DFA & 2 & 0.771871 & 0.776294 & 0.0053 \\ +DFA & 3 & 0.815630 & 0.814164 & 0.0052 \\ +FA & 0 & 0.647613 & 0.648186 & 0.005 \\ +FA & 1 & 0.591587 & 0.599896 & 0.0064 \\ +FA & 2 & 0.771871 & 0.777543 & 0.0055 \\ +FA & 3 & 0.815630 & 0.814227 & 0.0052 \\ +\bottomrule +\end{tabular} |