Reliability Analysis of Limited Failure One-Shot Devices
Why this work is in the frame
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Bibliographic record
Abstract
Meeker introduced the concept of limited failure population (LFP) while studying integrated circuits, where most devices exhibit a near-zero probability of failure throughout their technological life, while a small subset contains latent defects that manifest only after prolonged operation. In this article, we extend the LFP framework to the context of one-shot device testing, wherein devices get destroyed or must be rebuilt after testing. We propose a model that incorporates a relationship between defect probability and a set of covariates and develop an expectation–maximization algorithm for estimating the model parameters. The effectiveness of the proposed method is then assessed through a Monte Carlo simulation study, assuming the lifespan of defective devices follow a log-location-scale distribution. Finally, the developed methods are applied to three real datasets.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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