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Record W3113158417 · doi:10.1522/revueot.v29n3.1196

La santé numérique : un levier pour améliorer l’accessibilité aux soins de santé au Québec

2020· article· fr· W3113158417 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueRevue Organisations & territoires · 2020
Typearticle
Languagefr
FieldHealth Professions
TopicHealthcare Systems and Practices
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsPolitical scienceMedicineHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

L’accessibilité aux soins de santé est une problématique importante au Québec. Aujourd’hui, le développement des technologies dans le secteur de la santé offre des possibilités intéressantes pour améliorer l’accessibilité aux soins de santé. L’objectif de cette recherche est d’identifier les options qu’offre la santé numérique pour améliorer l’accessibilité aux services de soins de santé au Québec, plus particulièrement dans les régions éloignées. Cette étude montre que la santé numérique offre des bénéfices à la fois pour les patients et pour les professionnels de la santé, et qu’elle favorise l’accessibilité aux soins de santé dans les régions rurales de la province. Les barrières devant être franchies afin d’assurer un accès aux services de santé à l’ensemble de la population québécoise sont également identifiées.

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.

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)0.003
metaresearch head score (Gemma)0.007
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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.803
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0090.002

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 head0.070
GPT teacher head0.412
Teacher spread0.342 · 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