Bootstrap Support Is Not First-Order Correct
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The appropriate interpretation of bootstrap support for splits and the question of what constitutes large bootstrap support have received considerable attention. One desirable interpretation, indeed the interpretation that was put forward when bootstrap support for splits was first introduced, is that 1-minus bootstrap support is a P value for the hypothesis that the split is not well resolved. As a P value, bootstrap support has been argued to be first-order correct. By obtaining the limiting distribution of bootstrap support for a split when maximum likelihood estimation is conducted, it is shown that bootstrap support is not first-order correct and insight is provided into the nature of the problem. Borrowing from earlier results, it is also shown that similar results hold when the neighbor-joining algorithm is used. Examples suggest that bootstrap support is generally conservative as a P value and give insight as to why this is usually the case. The analysis indicates that the problem is largely due to the unusual nature of tree space where boundary trees always have at least 2 neighbors.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it