Module complexe des enrobés et module réversible des matériaux granulaires pour le dimensionnement mécaniste-empirique des chaussées au Québec
Bibliographic record
Abstract
Le ministere des Transports du Quebec a elabore des methodes d’essai pour la determination du module complexe des enrobes et du module reversible des materiaux granulaires. Le MTQ a egalement cree une banque de donnees de module complexe pour les enrobes et de module reversible pour les materiaux granulaires a partir des expertises realisees au cours des sept dernieres annees. Cette banque de donnees a pour objectif d’aider les expertises sur les materiaux et le dimensionnement mecaniste-empirique des chaussees au MTQ. Elle pourrait egalement servir de guide pour optimiser les specifications sur les enrobes et les materiaux granulaires, ainsi que le dimensionnement des chaussees au Quebec. L’article presente les methodes d‘essais, les valeurs de module complexe et de module reversible typiques obtenues, ainsi que les principales observations concernant les types de materiaux etudies. La banque compte actuellement 76 enrobes formules avec differentes granulometries et differents types de bitume, avec certains enrobes contenant des ajouts. La banque inclus egalement 54 materiaux granulaires de mineralogies et de granulometries differentes, avec certains materiaux granulaires incluant egalement des ajouts.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".