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Record W2787284104 · doi:10.4000/books.pum.7186

Comprendre l’influence des gestes quotidiens pour en faire le prolongement des interventions en matière de prescription d’exercices

2013· book-chapter· fr· W2787284104 on OpenAlexafffund
Martine Leblanc

Bibliographic record

VenuePresses de l’Université de Montréal eBooks · 2013
Typebook-chapter
Languagefr
FieldSocial Sciences
TopicFrench Language Learning Methods
Canadian institutionsCegep de Trois-Rivieres
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchUniversité de MontréalRoyal CaninZoetis
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Les personnes auprès desquelles j’interviens présentent en majorité des douleurs d’origine musculosquelettiques (tendinites variées, lombalgie, cervicalgie, hernie discale, arthrite, fibromyalgie, etc.). Parmi elles, celles qui font le lien entre les exercices pratiqués en cours et leurs occupations quotidiennes semblent démontrer de meilleurs résultats en matière de guérison, de diminution de la douleur et de l’amélioration de leur condition physique générale.Au-delà de ce constat, qui me s...

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)0.003
metaresearch head score (Gemma)0.008
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: Other · Consensus signal: Other
Teacher disagreement score0.013
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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.

Opus teacher head0.020
GPT teacher head0.244
Teacher spread0.224 · 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
GenreOther

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

Citations0
Published2013
Admission routes2
Has abstractyes

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