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Record W4206847392 · doi:10.46298/pspa.14142

Le Centre d’Innovation du partenariat avec les patients et le public: Un moteur du développement de la culture du partenariat de soin avec le patient, avec les patients et le public en Europe

2020· article· fr· W4206847392 on OpenAlexaffabout
Luigi Flora, Jean-Michel Benattar, David Darmon

Bibliographic record

Venue˜Le œPartenariat de soin avec le patient. · 2020
Typearticle
Languagefr
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

Un centre d’innovation sur le partenariat avec les patients et le public a vu le jour au printemps 2019, au sein même de la faculté de médecine de l’Université Côte d’Azur. Ce centre est le fruit d’une conjonction de rencontres et circonstances entre l’action d’une association citoyenne mettant en œuvre depuis 2015 des rencontres d’éducation populaire, questionnant les grands enjeux de santé concernant l’ensemble des citoyens, la rencontre de son fondateur avec des coconcepteurs du modèle de Montréal (Pomey et al, 2015) et la faculté de médecine de l’Université Côte d’Azur. Cet article, prolongement de la conférence de clôture du premier congrès international sur le partenariat avec les patients et le public en France qui s’est déroulé à Nice les 14 et 15 octobre 2019, éclaire la genèse de cette entité novatrice en France, de son mode d’organisation et de ses missions.

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)0.025
metaresearch head score (Gemma)0.021
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 score0.065
Threshold uncertainty score0.189

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0160.023
Scholarly communication0.0270.013
Open science0.0020.018
Research integrity0.0060.009
Insufficient payload (model declined to judge)0.0120.002

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 head0.058
GPT teacher head0.302
Teacher spread0.244 · 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

Citations1
Published2020
Admission routes2
Has abstractyes

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