One‐sided Control Charts Based on Precedence and Weighted Precedence Statistics
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Bibliographic record
Abstract
In this paper, we study one‐sided control charts based on precedence statistics. Because we focus on the problem of detecting ‘smaller’ lifetime than expected, we consider only one‐sided control charts that have not received much attention in the literature. Alarm rate and average run length are derived when the process is in control and also when the process is out of control for two Lehmann alternatives. On the basis of the alarm rate and average run length, we propose suitable randomized procedures to determine the best precedence control chart. Control charts based on weighted precedence statistics are then studied. The charts developed here are illustrated with coal mining disasters data. Finally, a comparison of the performance of these two charts is made with that of a Wilcoxon–Mann–Whitney control chart and a cumulative sum chart based on the precedence statistic, and some conclusions are drawn. Copyright © 2014 John Wiley & Sons, Ltd.
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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 | 0.003 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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