Quality assurance through truncated life tests under the Lomax distribution
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Sampling inspection plan is a valuable tool used across industries to ensure product quality, comply with regulatory standards, and maintain cost efficiency in quality control processes. To check for defects in the products during production, a batch of goods produced may be inspected through sampling to decide whether to accept or reject the entire batch based on the quality level of the sample. In this study we develop acceptance sampling plans based on truncated life tests utilizing the Lomax distribution. The study analyzes different parameters of the Lomax distribution to determine the minimum sample sizes necessary for evaluating the quality of lots or production processes. Additionally, we calculate the operating characteristic function values and establish the minimum ratio of the true mean life to the specified mean life of the product, taking into account the risks faced by both consumers and producers with our proposed sampling method. The effectiveness of these sampling plans is demonstrated through their application to real-world data, assessing their practical utility in quality evaluation.
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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 | 0.005 |
| 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 | 0.000 |
| 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