Prendre en charge la douleur chronique
Bibliographic record
Abstract
Cet ouvrage présente les nouvelles thérapeutiques non médicamenteuses efficaces dans la prise en charge de la douleur : hypnose, thérapies cognitivo-comportementales, mindfullness, EMDR, thérapie d'acceptation et d'engagement, etc. Il s'agit donc de manière plus large d'apporter une compréhension globale dans le domaine de la douleur à tous les professionnels de santé et étudiants, leur permettant de s'initier et de s'ouvrir à des méthodes de prises en charge novatrices. Avec Fanny Bassan, Psychologue clinicienne, psychothérapeute libérale. Antoine Bioy, Professeur des Universités, psychologue clinicien, hypnothérapeute. Marion Trousselard et Charles Martin Krumm, Professeur des universités. Frédérick Dionne et Josée Veillette, PhD à l’université de Québec. Jean Michel Gurret, psychologue, formateur EFT. François Laroche, Professeur, responsable du Centre d’Évaluation et de Traitement de la Douleur, Hôpital Saint Antoine Paris
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.034 | 0.012 |
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".