MétaCan
Menu
Back to cohort
Record W1982615281 · doi:10.1016/j.hcmf.2011.02.010

La prise de décision fondée sur des données probantes en santé publique

2011· article· fr· W1982615281 on OpenAlexaboutno aff
Megan Ward

Bibliographic record

VenueHealthcare Management Forum · 2011
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicOrganizational Change and Leadership
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

On a créé un processus pour appliquer systématiquement la recherche aux décisions de santé publique dans une grande organisation de santé publique du Canada. Ce processus en neuf étapes est soutenu par des outils et une formation pour accéder à la recherche, l'évaluer et l'appliquer. Il a été mis en œuvre dans l'ensemble de l'organisation selon les principes de la théorie de gestion du changement élaborée par Kotter et Cohen.

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)0.135
metaresearch head score (Gemma)0.293
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.135
Threshold uncertainty score0.714

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1350.293
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0100.006
Science and technology studies0.0070.008
Scholarly communication0.0240.012
Open science0.0030.006
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0070.001

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 head0.075
GPT teacher head0.262
Teacher spread0.187 · 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
GenreEmpirical

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
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueHealthcare Management ForumSame topicOrganizational Change and LeadershipFrench-language works237,207