Exact Nonparametric Two-Sample Homogeneity Tests for Possibly Discrete Distributions
Why this work is in the frame
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Bibliographic record
Abstract
Dans ce texte, nous tudions plusieurs tests pour l'galit de deux distributions inconnues.Deux de ces tests sont bass sur des fonctions de distribution empiriques, trois autres sur des estimateurs non paramtriques de fonctions de densit et les trois derniers sur des moments empiriques.Nous proposons de contrler la taille des tests (sous des hypothses non paramtriques) en employant des versions permutationnelles de ces tests conjointement avec la mthode des tests de Monte Carlo ajuste pour tenir compte de la possibilit de distributions discontinues.Nous proposons aussi une mthode pour combiner plusieurs de ces tests, le niveau de ces procdures tant aussi contrl par la technique des tests de Monte Carlo, laquelle possde de meilleures proprits de puissance que les tests individuels combins.Finalement, nous montrons dans une tude de simulation que la technique suggre contrle parfaitement la taille des diffrents tests considrs et que les nouveaux tests proposs peuvent fournir de notables amliorations de puissance.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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