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Record W4403144647 · doi:10.1007/s10286-024-01070-z

In at the deep end: the physiological challenges associated with artistic swimming

2024· letter· en· W4403144647 on OpenAlexafffund
Emma L. Williams, C.J. Mathias, Shubhayan Sanatani, Mike Tipton, Victoria E. Claydon

Bibliographic record

VenueClinical Autonomic Research · 2024
Typeletter
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsBC Children's HospitalBoucher Institute of Naturopathic MedicineSimon Fraser UniversityRoyal Columbian Hospital
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNeurologyMedicineDiabetes mellitusNeurosciencePsychologyPsychiatryEndocrinology

Abstract

fetched live from OpenAlex

Artistic swimming • Autonomic conflict • Exercise • SyncopeArtistic (synchronized) swimming is an Olympic sport that combines skills of swimming, dance, weightlifting, cheerleading, and gymnastics.In competition, athletes are required to perform routines comprised of elaborate movements in the water, synchronized to music, which last from 2 to 5 min [1].These require athletes to perform sustained vigorous exercise with intermittent prolonged breath-holds that can cumulatively account for 50% or more of their entire routine [2].By combining breath-holding with near-maximal physical output, artistic swimming provides a significant and unique physiological stress.The specific nature of this stress is poorly understood, in part due to the challenge of making physiological measurements underwater, methodological inconsistencies across investigations conducted to date [3][4][5][6][7], and the rapid evolution of the sport's complexity and difficulty since it was introduced into the Olympic program in 1984 [3].The complex physiological paradigm of artistic swimming is further compounded by the simultaneous provocation of conflicting sympathetic "fight and flight" and parasympathetic "rest and digest" responses, with * V.

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)0.001
metaresearch head score (Gemma)0.005
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 score0.012
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0120.011
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 head0.339
GPT teacher head0.471
Teacher spread0.131 · 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

Citations3
Published2024
Admission routes2
Has abstractyes

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