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Record W2947761280 · doi:10.1186/s40798-019-0190-3

A Physiological Overview of the Demands, Characteristics, and Adaptations of Highly Trained Artistic Swimmers: a Literature Review

2019· review· en· W2947761280 on OpenAlexaff
Eric Viana, David J. Bentley, Heather M. Logan-Sprenger

Bibliographic record

VenueSports Medicine - Open · 2019
Typereview
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsCanadian Sport Centre PacificOntario Tech University
Fundersnot available
KeywordsEliteAthletesAdaptation (eye)Physiological AdaptationsPsychologyElite athletesApplied psychologyPhysical medicine and rehabilitationCognitive psychologyPhysical therapyMedicineNeuroscienceEcologyBiologyPolitical science

Abstract

fetched live from OpenAlex

Artistic swimming (AS) is a very unique sport consisting of difficult artistically choreographed routines ranging in the number of athletes (one to ten: solo, duet, team, combination, highlight routine) and with elements performed quickly and precisely above, below, and on the surface of the water. As a result, the physical and physiological demands placed on an athlete are unique to the sport with the most pronounced adaptation being the bradycardic response to long apneic periods spent underwater while performing strenuous movements. This indeed influences training prescription and the desired training outcomes. This review paper explores the physiological demands of AS, the physiological characteristics that influence AS performance, and innovative approaches to enhancing training and performance in elite performers.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.159
GPT teacher head0.406
Teacher spread0.247 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations35
Published2019
Admission routes1
Has abstractyes

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