A Sieve Bootstrap Two-Sample<i>t</i>-Test Under Serial Correlation
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Bibliographic record
Abstract
The classical two-sample t-test assumes that observations are independent. A violation of this assumption could lead to unreliable or even erroneous conclusions. However, in many biological studies, data are recorded over time and hence exhibit serial correlation. In order to take such temporal dependence into account, we suggest applying the sieve bootstrap method to generate replications of the observed data and then using these proxy-dependent processes to construct the empirical distribution for the t-statistic. The proposed method is fast, distribution-free, and well approximates the nominal significance level. We illustrate our approach in application to detection problem of brain activity in functional magnetic resonance imaging (fMRI) and a longitudinal study of weight growth in rats.
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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 | 0.008 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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