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Record W2551405295 · doi:10.1136/bjsports-2016-096994

Exercise prescription is not just for medical doctors: the benefits of shared care by physicians and exercise professionals

2016· letter· en· W2551405295 on OpenAlexaboutno aff
Andrew Maiorana, Itamar Levinger, Kade Davison, Neil A. Smart, Jeff S. Coombes

Bibliographic record

VenueBritish Journal of Sports Medicine · 2016
Typeletter
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsnot available
Fundersnot available
KeywordsMedical prescriptionMedicineFamily medicineExercise prescriptionSports medicinePhysical activityHealth carePopulationPosition statementIntervention (counseling)Alternative medicineHealth professionalsPhysical therapyNursing

Abstract

fetched live from OpenAlex

As allied health professionals, we commend the Canadian Academy of Sport and Exercise Medicine (CASEM) on their recent position statement to better equip physicians for physical activity prescription. The CAESM call on physicians to be more engaged in physical activity prescription to reduce the burden of non-communicable diseases associated with physical inactivity. Physicians are uniquely positioned in healthcare systems to improve population levels of physical activity.

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)0.008
metaresearch head score (Gemma)0.066
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.057
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.066
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0080.006
Scholarly communication0.0050.010
Open science0.0020.003
Research integrity0.0570.048
Insufficient payload (model declined to judge)0.0090.005

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 head0.028
GPT teacher head0.310
Teacher spread0.282 · 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
GenreCommentary

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

Citations25
Published2016
Admission routes1
Has abstractyes

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