Réhabilitation sismique des piliers de ponts rectangulaires à l'aide de chemises en PRFC
Bibliographic record
Abstract
Modes de rupture des piles de pont en béton armé -- Séismologie du Canada -- Ductilité -- Caractéristiques de la zone de chevauchement d'armatures -- Évolution de la conception sismique du code S6 -- Méthodes de renforcement des piliers de pont -- Effets de la vitesse de chargement et de la température -- Essais en laboratoire sur des piliers de pont à grande échelle -- Développement du montage expérimental -- Description générale du montage expérimental -- Conception des semelles -- Conception d'un dispositif d'application de la charge axiale -- Essais sur piles de grande dimension -- Description et objectifs du programme expérimental -- Conception et construction des spécimens -- Réparation de spécimen 3 -- Protocole et montage expérimental -- Calculs théoriques de résistance -- Résultats de l'essai sur le pilier de référence -- Réalisation de l'essai de S3 -- Réparation du spécimen 4 -- Réalisation de l'essai de S4 -- Analyse des résultats -- Rappel de la problématique et des objectifs du projet de recherche -- Conclusions du développement du montage expérimental -- Conclusions des essais sur piles de grande dimension -- Recommandations pour les recherches futures.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.007 | 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".