The Predictability of Aircraft Failures with Age
Bibliographic record
Abstract
<div class="htmlview paragraph">An aircraft is a complex operating system subject to the aging and degeneration processes. It is also maintained and repaired to keep operational condition high. Declining condition increases the chance of failures. Since repair is typically variable and incomplete, the question of the reliability of aircraft as they age is significant.</div> <div class="htmlview paragraph">In this paper the predictability of failures of aircraft as they age is considered. The methodology is to consider moderate mechanical failures which result in unscheduled landings. The records of a single aircraft model:B737 for a carrier whose fleet has large numbers of that model are analyzed. A Poisson regression model is fitted to the number of unscheduled landings over a 3 year period, with the rate depending on age and periodic maintenance. A clear age pattern emerges. Although the rate of decline depends on the model, and the rate of improvement through repair depends on the carrier, the aging is real since these factors are held constant.</div>
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 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".