Bibliographic record
Abstract
Les dentistes de la province de Québec constituent une sous-population bien définie dont l’étude est devenue très importante pour une bonne planification. On a constaté que la mauvaise répartition des dentistes fait obstacle à la réalisation de la gratuité des soins dentaires. En effet, la plupart des dentistes ont tendance à s’établir dans les grands centres, tendance qui semble s’accentuer depuis les dix dernières années. Une étude de la population selon certaines caractéristiques socio-démographiques a amené l’auteur à diviser le Québec en huit régions homogènes à partir d’un regroupement des divisions de recensement. C'est à partir de ces huit régions qu’il a illustré l’évolution future de l’offre de soins en considérant le rapport dentistes/population. Il a donc fallu procéder à une projection du nombre des dentistes d’une part et de la population d’autre part à l’aide de deux modèles de projection multirégionale. La méthode de regroupement et les projections démographiques font maintenant partie intégrante de l’étude de l’offre de services dentaires au Québec.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".