Strongly Connected Components in graphs, formal proof of Tarjan1972 algorithm
Bibliographic record
Abstract
Nous presentons une preuve formelle de l'algorithme de Tarjan (1972) pour trouver les composantes fortement connexes dans un graphe. Cet algorithme execute une seule passe sur le graphe le parcourant en profondeur d'abord. Notre programme est ici ecrit dans un style de programmation fonctionnelle dans le langage Why3-ML. La preuve utilise des lemmes et des assertions exprimes dans la logique de Why3. La majorite d'entre eux sont prouves automatiquement a l'exception de 5 assertions ou lemmes prouves manuellement en Coq. Une preuve d'une version imperative de ce programme ne figure pas dans ce travail, mais nous indiquons comment y parvenir par raffinements successifs. Un point important est que nos preuves sont intuitives, publiables et lisibles par un humain.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".