Note de lecture de l'ouvrage de Michèle Sirois (sous la direction scientifique de Sylvie Belleville) (2017). Vieillir en santé, c'est possible ! Montréal : Collection Institut universitaire de gériatrie de Montréal du Centre-Sud-de-l'île-de-Montréal
Bibliographic record
Abstract
Cet ouvrage collectif de vulgarisation scientifique rédigé sous la plume avertie de Michelle Sirois, auteure-coordonatrice ainsi que collaboratrice attitrée de longue date à la diffusion des connaissances au Centre de recherche à l'Institut universitaire de gériatrie de Montréal (IUGM), présente un texte solide et énergique au sujet du bien-vieillir dans le contexte social du vieillissement de la population.Ces textes tels que proposés sont en outre co-dirigés par Sylvie Belleville, chercheuse au centre de recherche de cette même infrastructure organisationnelle universitaire ainsi que professeure titulaire au Département de psychologie de l'Université de Montréal.
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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.054 | 0.033 |
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".