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Record W4313824634 · doi:10.31083/j.rcm2401014

Cardiorespiratory Fitness and Its Place in Medicine

2023· review· en· W4313824634 on OpenAlex
Robert Ross, Jonathan Myers

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueReviews in Cardiovascular Medicine · 2023
Typereview
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsQueen's University
Fundersnot available
KeywordsCardiorespiratory fitnessMedicineGuidelineIntensive care medicinePhysical therapyDiseaseCardiorespiratory arrestPosition (finance)Internal medicineSurgeryPathology

Abstract

fetched live from OpenAlex

The evidence that cardiorespiratory fitness (CRF) predicts morbidity and mortality independent of commonly obtained risk factors is beyond dispute. Observations establishing that the addition of CRF to algorithms for estimating cardiovascular disease risk reinforces the clinical utility of CRF. Evidence suggesting that non-exercise estimations of CRF are associated with all-cause mortality provides an opportunity to obtain estimates of CRF in a cost-effective manner. Together with the observation that CRF is substantially improved in response to exercise consistent with guideline recommendations underscores the position that CRF should be included as a routine measure across all health care settings. Here we provide a brief overview of the evidence in support of this position.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.876
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0260.005
Bibliometrics0.0020.004
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.136
GPT teacher head0.390
Teacher spread0.254 · 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