Démarche d'aide à la conception par approche multimode des SED
Bibliographic record
Abstract
Base sur la theorie du controle par supervision (TCS), nous proposons une demarche d'aide a l'etude de la dynamique des Systemes a Evenements Discrets (SED). Situee en amont du cycle de conception des lois de commande des SED, notre proposition concerne la gestion des modes de fonctionnement. L'objectif est de permettre tout d'abord l'etude formelle de la dynamique du systeme controle dans chaque mode puis celle de la succession de ces dynamiques. Dans cet article nous insisterons particulierement sur la presentation des differentes etapes de construction et de generation automatique des modeles ainsi que sur les possibilites de validation de ceux-ci. Based on the Supervisory Control Theory, this paper introduces a framework to help study the dynamics of Discrete Event Systems (DES). Upstream of the design process of control law in DES, the proposal focuses on the management modes of operation. The goal is to first allowing a formal study of the controlled system's dynamics in each mode and secondly studying the mode switching. This article is focused on the presentation of the different stages of design, the automatic generation of models and the possibilities of validating them.
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How this classification was reachedexpand
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".