An optimal burn‐in preventive‐replacement model associated with a mixture distribution
Why this work is in the frame
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Bibliographic record
Abstract
Abstract A mixture arises in a number of situations. A typical situation is that a population is heterogeneous and consists of several sub‐populations, which represent mutually exclusive failure modes (usually early failures where the mean time to failure (MTTF) is ‘short’ and wear‐out failures where the MTTF is ‘long’ and the hazard rate is increasing). When the time to failure of an item follows a mixture distribution, it is difficult to determine an appropriate operational or/and maintenance policy to reduce the early‐phase failures and field operational cost. This paper examines the effectiveness of jointly applying a burn‐in procedure and preventive replacement policy to such items, and discusses implementation‐related issues associated with the combined policy. A numerical example is also included. Copyright © 2007 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 | 0.001 | 0.000 |
| 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