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Record W1548198485 · doi:10.14288/hfjc.v4i2.104

Executive Summary: The 2011 Physical Activity Readiness Questionnaire for Everyone (PAR-Q+) and the Electronic Physical Activity Readiness Medical Examination (ePARmed-X+)

2011· article· en· W1548198485 on OpenAlexaff
Darren E. R. Warburton, Veronica Jamnik, Shannon S. D. Bredin, Jamie F. Burr, Sarah Charlesworth, Phil Chilibeck, Neil D. Eves, Heather J.A. Foulds, Jack M. Goodman, Lee W. Jones, Donald C. McKenzie, Ryan E. Rhodes, Michael C. Riddell, Roy J. Shephard, James A. Stone, Scott Thomas, E. Paul Zehr, Norman Gledhill

Bibliographic record

VenueOpen Collections · 2011
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsUniversity of CalgaryUniversity of VictoriaUniversity of SaskatchewanUniversity of TorontoYork UniversityUniversity of British Columbia
Fundersnot available
KeywordsPhysical activityHealth professionalsExecutive summaryPsychologyMedicinePhysical therapyHealth careBusiness

Abstract

fetched live from OpenAlex

This summary outlines the recent process employed to reduce barriers to physical activity participation for all persons (including those with established chronic disease and/or disability). These screening tools are intended for persons interested in becoming more physically active, allied health professionals, qualified exercise professionals, and physicians alike. Following is a point-by-summary of the process, the key recommendations and new risk stratification strategy, and the changes made to the pre-exercise screening forms. Further information regarding this process can be found at www.eparmedx.com.

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)0.009
metaresearch head score (Gemma)0.029
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.088
Threshold uncertainty score0.295

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.029
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.006
Science and technology studies0.0010.000
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0880.096

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 head0.044
GPT teacher head0.331
Teacher spread0.287 · 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

Citations18
Published2011
Admission routes1
Has abstractyes

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