Dispatch analysis automation of the aircraft engine control system
Bibliographic record
Abstract
Les redondances présentes dans le système de régulation d'un moteur d'avion permettent d'autoriser des configurations de fonctionnement avec certaines pannes, afin d'améliorer sa disponibilité. L'analyse de disponibilité doit néanmoins respecter la réglementation CS-E afin d'assurer un niveau de sécurité acceptable. L'outil présenté modélise l'événement redouté de perte de contrôle de la poussée et s'appuie sur l'analyse markovienne. Il permet de déterminer de manière automatique les durées de fonctionnement avant réparation des pannes simples et multiples du système. Cet outil prend en entrée la description fonctionnelle du système de régulation (acquisitions des données moteur et commandes des actionneurs). L'outil étudie toutes les combinaisons de panne du système afin de déterminer tous les états du graphe de Markov. Ils sont obtenus en étudiant le « lien de parenté » des organes considérés dans la combinaison de panne.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Simulation or modeling | low |
| gpt | no category Domain: not available · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Simulation or modeling | low |
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".