MétaCan
Menu
← Back to cohort
Record W7092299315 · doi:10.71781/51

Vieillir au Québec : perspectives de la recherche

2025· book· fr· W7092299315 on OpenAlexaboutno aff

Bibliographic record

VenueOpen MIND · 2025
Typebook
Languagefr
FieldHealth Professions
TopicAging, Elder Care, and Social Issues
Canadian institutionsnot available
Fundersnot available
KeywordsEconomic JusticeContext (archaeology)Subject (documents)Perspective (graphical)

Abstract

fetched live from OpenAlex

Le Livre blanc Vieillir au Québec : Perspectives de la recherche propose une feuille de route pour une recherche de haut calibre, caractérisée par l’excellence et l’innovation tout en étant éclairée par les expertises multiples et la voix même des personnes concernées. Au-delà d’un état des lieux, ce Livre blanc est un appel à l’action, invitant citoyennes et citoyens, chercheuses et chercheurs, décideuses et décideurs ainsi qu’entrepreneures et entrepreneurs à conjuguer leurs efforts pour faire du vieillissement une source d’innovation, de justice et de prospérité pour toute la société québécoise.

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 imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.128
Threshold uncertainty score0.927

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.006
Science and technology studies0.0170.014
Scholarly communication0.0140.006
Open science0.0020.002
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0210.001

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.

Opus teacher head0.268
GPT teacher head0.510
Teacher spread0.242 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueOpen MIND→Same topicAging, Elder Care, and Social Issues→French-language works237,207→