MétaCan
Menu
Back to cohort
Record W2033930277 · doi:10.1177/000841740607300405

Étude de fidélité test-retest de L'Évaluation des Capacités Physiques reliées au Travail

2006· article· fr· W2033930277 on OpenAlexaffvenue
Bruno Brassard, Marie‐José Durand, Patrick Loisel, Jacques Lemaire

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2006
Typearticle
Languagefr
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsReliability (semiconductor)PsychologyKappaTest (biology)Physical therapyPsychometricsClinical psychologyMedicineMathematics

Abstract

fetched live from OpenAlex

BACKGROUND: Functional capacity evaluations are used to quantify and qualify the physical abilities of an individual in relation to the physical requirements of an occupation. One major observation associated with functional capacity evaluations is a lack of evidence on their psychometric properties. PURPOSE: This article presents the results of a study on the test-retest reliability of a functional capacity evaluation tool: the Physical Work Performance Evaluation (PWPE). The PWPE is an instrument for evaluating the physical work capacities of individuals with physical limitations resulting from a health problem. METHODS: The PWPE was administered twice to a convenience sample of 30 workers in good health. RESULTS: In the section on 'Dynamic Strength', the tasks demonstrate a good test-retest reliability (0.79 < ICC < 0.91). The three sections and the global score of the PWPE demonstrate a moderate stability (0.43 < kappa > 0.52). PRACTICE IMPLICATIONS: The PWPE score should be interpreted with caution and further studies on its psychometric properties will be necessary to clarify its clinical utility.

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)0.071
metaresearch head score (Gemma)0.167
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.374

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0710.167
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.002
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.059
GPT teacher head0.347
Teacher spread0.288 · 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 designObservational
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

Citations3
Published2006
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Occupational TherapySame topicMusculoskeletal pain and rehabilitationFrench-language works237,207