Bibliographic record
Abstract
La province de Quebec est tres attractive pour les Francais de par sa culture et sa langue. Elle suscite curiosite et envie de nombreux chirurgiens-dentistes Francais. Le 7 octobre 2008, a ete signe un accord France-Quebec, en matiere de reconnaissance mutuelle des qualifications professionnelles. Malgre cet accord, il n'est pas chose simple pour un dentiste forme en France de s'installer au Quebec car de nombreuses differences sont presentes. En effet, la formation de chirurgie dentaire au Quebec diverge par ses conditions d'admission, sa duree, son programme d'apprentissage theorique et pratique ainsi que par son cout. Par ailleurs, l'approche par competence est largement privilegiee dans la formation de la medecine dentaire au Canada depuis les annees 1990, ou l'enseignement devient finalement un apprentissage. Dans ces deux endroits, la poursuite des etudes de 3eme cycle en France et 2eme cycle au Quebec est possible notamment dans des specialites telles que la dentisterie multidisciplinaire, la chirurgie buccale et maxillo-faciale, la gerodontologie, la parodontie et l'endodontie. A cela s'ajoute des disparites dans l'organisation et dans la composition de l'equipe du cabinet dentaire qui est plus diversifiee, repondant aux besoins de la population en matiere de sante buccodentaire. Enfin, les systemes d'acces aux soins sont differents en ce qui concerne les assurances de sante publiques et privees chargees de la prise en charges des soins dentaires.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.006 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".