facap.git/outputs/tables, branch main Unnamed repository; edit this file 'description' to name the repository. Track legacy operator-study row data; extend generated tables 2026-07-28T16:15:44+00:00 haoyuren 13851610112@163.com 2026-07-28T16:15:44+00:00 103a9413d025482f408d758fe6612e2c36cc265a Pulls the training-set-size series, snapshot-location sweep, stress grid, scalar-gain comparison, oracle diagnostic, and derivative-probe rows from the experiment machine, and adds three generated fragments (train size, snapshot location, stress grid) used by the appendix. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> 
Pulls the training-set-size series, snapshot-location sweep, stress
grid, scalar-gain comparison, oracle diagnostic, and derivative-probe
rows from the experiment machine, and adds three generated fragments
(train size, snapshot location, stress grid) used by the appendix.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Add cluster bootstrap metrics, supplementary finite-time figure, teacher nested SEs 2026-07-28T15:31:36+00:00 haoyuren 13851610112@163.com 2026-07-28T15:31:36+00:00 489da71c7af8304a86ed761359614d71288425cf finite_time_supplement.py computes 95% cluster bootstrap intervals for the predictor metrics (resampling forward initializations within each cell) and renders the six-panel supplementary figure. The table generator gains the teacher-task nested-SE fragment, computed from the raw paired rows pulled from the experiment machine. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> 
finite_time_supplement.py computes 95% cluster bootstrap intervals for
the predictor metrics (resampling forward initializations within each
cell) and renders the six-panel supplementary figure. The table
generator gains the teacher-task nested-SE fragment, computed from the
raw paired rows pulled from the experiment machine.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Add appendix table generator and generated LaTeX fragments 2026-07-28T13:17:38+00:00 haoyuren 13851610112@163.com 2026-07-28T13:17:38+00:00 3b5f01cb4db9efc4ceb2ba17709bbfc82a63e660 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> 
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>