Bibliographic record
Abstract
Ce papier vise à estimer un modèle logit mixte pour analyser les choix virtuels des consommateurs canadiens lorsqu’ils font face à de nouvelles technologies de transport utilisant des carburants de remplacement. Pour ce faire, nous employons les données d’une étude sur les préférences déclarées des consommateurs canadiens en matière de transport réalisée en 2002 par le Energy and Materials Research Group à l’Université Simon Fraser. Ces données sont particulièrement bien adaptées à l’analyse de l’impact de nouvelles technologies et de sources d’énergie de remplacement pour lesquelles il n’existe pas encore de marché bien établi. Notre étude permet d’identifier les principaux déterminants des choix individuels en matière de nouvelles technologies de transport. Des simulations sont effectuées pour déterminer sur quels facteurs socioéconomiques il faudrait mettre l’accent dans l’élaboration de politiques visant à faciliter l’intégration des nouvelles technologies sur le marché canadien de l’automobile.
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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.025 | 0.005 |
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".