Validating the Reliability Simulation Using Bohlamp Circuit with Accelerated Life Test Method
Bibliographic record
Abstract
Learning media is very importance tools to achieved the learning outcome like capable to design reliability engineering system (RES). The students should be understanding with basic theory of reliability and also have technical skill based on need analysis. Unfortunately, the RES learning media are still not available specially to implement of several type of reliability system. Objective of the study is introducing reliability device model simulation with choice option series, parallel and combine series-parallel system. Method of the study are using accelerated life testing method (ALT) which has been analyzed with statistical method to estimate life-time at normal condition. Validating value of each reliability system are have similarity between experimental test (Re) and theoretical (Rt) i.e.: series (Rt=0.329; Re=0.359); parallel (Rt=0.976; Re=0.972.), and combined of series-parallel (Rt=0. 651; Re=0.686). The conclusion is the parallel have high-fidelity on application of reliability simulation with error 0.000409.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".