Prévention et dépistage du cancer du col de l?utérus" : Quelles recommandations pour quelle efficacité, tour d'horizon des pays européens et/ou anglo-saxons
Bibliographic record
Abstract
Le dossier technique consacre au depistage du cancer du col uterin a ete subdivise en deux parties : une premiere partie qui a permis d'obtenir un apercu general des pratiques de depistage a l'echelle europeenne et anglo-saxonne (Doumont D., Deccache C., Prevention et depistage du cancer du col de l'uterus : quelles recommandations pour quelle efficacite ? 1ere partie : Tour d'horizon des pays europeens et /ou anglo-saxons, Septembre 2011, Ref. 11-64, 40 pages) et une seconde partie qui s'est plus particulierement interessee aux pratiques et recommandations en matiere de depistage du cancer du col de l'uterus dans les pays suivants : la France, la Suisse, le Canada, les Pays-Bas et l'Angleterre.
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 | 0.014 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".