Avis de publication - Statistiques canadiennes sur le cancer
Bibliographic record
Abstract
Statistiques canadiennes sur le cancerDiffuser cet article sur Twitter Vient de paraître !Le rapport spécial de 2018 des Statistiques canadiennes sur le cancer a été publié le 13 juin 2018.Résultat d'un partenariat entre l'Agence de la santé publique du Canada, Statistique Canada et la Société canadienne du cancer, la publi cation des Statistiques canadiennes sur le cancer de cette année est un rapport spécial sur l'incidence du cancer selon le stade au moment du diagnostic.On y retrouve également un aperçu du cancer au Canada en fonction des estimations des Statistiques canadiennes sur le cancer 2017, ainsi qu'un guide pour trouver d'autres statistiques sur le cancer en utilisant la base de données en ligne de Statistique Canada, CANSIM.
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 | 0.020 | 0.136 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.011 | 0.027 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.159 | 0.059 |
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".