La place du patient dans l’environnement numérique : l’exemple de l’implication des patients partenaires avec le Centre d’Innovation du Partenariat de Soin avec les Patients et le Public (CI3P)
Bibliographic record
Abstract
Si la place des patients dans un environnement numérique prend chaque jour un peu plus de place dans les systèmes de santé, un environnement accéléré ces trois dernières années par l’impact de la pandémie mondiale de la Covid-19, diverses questions se posent tant au sujet des services proposés et de leur accessibilité qu’en terme d’acceptabilité sociale. Leur participation dans l’élaboration des moyens et services à mettre en œuvre à l’orée de la révolution des patients demandée il y a quelques années par le British Medical Journal , revue phare des revues de médecine basées sur les preuves ( Evidence Based medicine ) (Richards et al, 2013) 1 serait-elle une des réponses possibles ? C’est cette question qu’aborde cet article à travers l’exemple de ce que fédère le Centre d’Innovation du Partenariat avec les Patients et le Public (CI3P) de la faculté de médecine d’Université Côte d’Azur.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.015 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".