MétaCan
Menu
Back to cohort
Record W196470424 · doi:10.1007/s11724-014-0398-4

Traduction et adaptation de la version canadienne-française du Pain Management Activities Questionnaire (PMAQ)

2014· article· fr· W196470424 on OpenAlexaffabout
Dave A. Bergeron, Frances Gallagher, Patricia Bourgault

Bibliographic record

VenueDouleur et Analgésie · 2014
Typearticle
Languagefr
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsPsychology

Abstract

fetched live from OpenAlex

Les infirmières québécoises semblent actuellement peu impliquées dans la gestion de la douleur chronique alors que des modèles démontrent pourtant leur valeur ajoutée. Aucune étude n’a évalué les activités en gestion de la douleur. Pour effectuer une telle étude, un questionnaire évaluant leur réalisation est nécessaire. Cet article a pour but de décrire le processus de sélection, de traduction, d’adaptation et de validation du Pain Management Activities Questionnaire (PMAQ). Suite à ce processus, ce questionnaire possède une bonne validité de contenu et peut être maintenant utilisé afin d’évaluer les activités infirmières en gestion de la douleur aiguë ou chronique.

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)0.017
metaresearch head score (Gemma)0.037
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.871
Threshold uncertainty score0.257

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.037
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.002

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 head0.006
GPT teacher head0.246
Teacher spread0.240 · 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 designBench or experimental
Domainnot available
GenreMethods

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

Citations4
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueDouleur et AnalgésieSame topicMusculoskeletal pain and rehabilitationFrench-language works237,207