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Record W2049197285 · doi:10.1016/j.apmr.2013.05.015

Development of Evidence-Informed Physical Activity Guidelines for Adults With Multiple Sclerosis

2013· article· en· W2049197285 on OpenAlexafffund
Amy E. Latimer‐Cheung, Kathleen A. Martin Ginis, Audrey L. Hicks, Robert W. Motl, Lara A. Pilutti, Mary Duggan, Garry D. Wheeler, Ravin Persad, Karen Smith

Bibliographic record

VenueArchives of Physical Medicine and Rehabilitation · 2013
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsMcMaster UniversityMultiple Sclerosis Society of CanadaCanadian Society for Exercise PhysiologyQueen's University
FundersCanadian Institutes of Health ResearchOntario Neurotrauma Foundation
KeywordsQuality of life (healthcare)MedicineGuidelineExercise prescriptionEvidence-based medicineEvidence-based practicePhysical therapyPromotion (chess)Multidisciplinary approachPhysical activityMEDLINERehabilitationStakeholderPsychologyAlternative medicineNursing

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.124
metaresearch head score (Gemma)0.259
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: Methods · Consensus signal: none
Teacher disagreement score0.124
Threshold uncertainty score0.658

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1240.259
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0050.007
Bibliometrics0.0090.005
Science and technology studies0.0030.002
Scholarly communication0.0070.005
Open science0.0090.007
Research integrity0.0130.018
Insufficient payload (model declined to judge)0.0030.002

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 head0.184
GPT teacher head0.407
Teacher spread0.223 · 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
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

Citations338
Published2013
Admission routes2
Has abstractno

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