Outil d'aide à l'exploration des changements dans les comportments de mobilité des motréalais
Bibliographic record
Abstract
Peu importe le type de modele utilise, la prevision de la demande de transport s’appuie souvent sur une analyse detaillee des grandes tendances. La fiabilite des previsions est donc etroitement liee a la capacite de faire ressortir les tendances importantes observees dans ces enquetes ainsi qu’a la possibilite d’en expliquer les orientations possibles. Dans la region de Montreal, de grandes enquetes sur la mobilite de la population existent depuis 1970. Cet article a comme objectif de presenter un outil de consultation des tendances de la mobilite se basant sur les enquetes de 1987 a 2008. Plusieurs indicateurs sont disponibles et sont bases sur l’objet deplacement et l’objet chaine de deplacements. Quelques tendances observees de la mobilite des individus dans la region de Montreal y sont aussi presentees. Plusieurs constats ressortent de l’etude des tendances. Parmi celles-ci, l’annee 1998 semble etre un point d’inflexion pour plusieurs d’entre elles. Cet article permet aussi de constater que les chaines de deplacements semblent moins sensibles aux changements de tendances que les indicateurs bases sur les deplacements.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.026 | 0.003 |
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".