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Record W1975149402 · doi:10.1249/mss.0b013e318172ceec

Exercise and the Heart

2008· article· en· W1975149402 on OpenAlexaff
Keith George, Rob Shave, Darren E. R. Warburton, Jürgen Scharhag, Greg Whyte

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2008
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Effects of Exercise
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAthletesRelevance (law)UnderpinningBroad spectrumPsychologyMedicineSports medicineDepression (economics)Physical therapyPolitical scienceEngineering

Abstract

fetched live from OpenAlex

Reports that participation in prolonged exercise can lead to a transient depression in ventricular function and/or a minor increase in biomarkers of cardiomyocyte insult have stimulated significant media and scientific attention in the last few years. Despite being of relevance to the scientist, the clinician, and a broad spectrum of athletes, these phenomena are poorly defined and controversial. Specifically, the definition and the description of these topics are quite limited, and conflicting data are available. Further, the mechanisms underpinning these events are not clear. Finally, a clear message related to the short- and the long-term impact on cardiovascular health and/or sports performance is lacking. The symposium "Exercise and the heart: Can you have too much of a good thing?" was presented at the ACSM Annual Meeting in New Orleans on June 1, 2007 to specifically address these issues. This initial introduction sets out the background to the main articles that will document our current understanding of these problems as well as suggest important avenues for further research.

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)0.000
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.002

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 head0.012
GPT teacher head0.265
Teacher spread0.253 · 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

Citations19
Published2008
Admission routes1
Has abstractyes

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