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Record W2038175026 · doi:10.7202/1012336ar

Agir! Pour ma santé : une interven- tion harmonisant services médicaux et services communautaires pour les Franco-Manitobains souffrant de dépression

2012· article· fr· W2038175026 on OpenAlexaffvenue
Danielle de Moissac, Monique Bohémier, Chelsea Herdman, Margaux Roch-Gagné, Julie Paillé, Christine Johnston, Michelle Arpin-Molinski, Georgette Dupuis, Mélanie Saint-Hilaire, Liliane Prairie

Bibliographic record

VenueReflets Revue d’intervention sociale et communautaire · 2012
Typearticle
Languagefr
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsUniversité de Saint-Boniface
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Agir! Pour masanté : une interven- tion harmonisant services médicaux et services communautaires pour les Franco-Manitobains souffrant de dépression. Un article de la revue Reflets (L’intervention communautaire chez les francophones minoritaires : des pratiques à découvrir) diffusée par la plateforme Érudit.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.333
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.002
Open science0.0020.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.002

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 head0.142
GPT teacher head0.451
Teacher spread0.309 · 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; both teacher heads agree on what is shown here.

Study designObservational
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

Citations2
Published2012
Admission routes2
Has abstractyes

Explore more

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