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Record W4205436878 · doi:10.1177/17479541211054458

Low Energy Availability and Relative Energy Deficiency in Sport: What Coaches Should Know

2022· article· en· W4205436878 on OpenAlexaff
Braeden T. Charlton, Sara Forsyth, David C. Clarke

Bibliographic record

VenueInternational Journal of Sports Science & Coaching · 2022
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsUniversity of British ColumbiaSimon Fraser University
Fundersnot available
KeywordsFemale athlete triadTriad (sociology)AthletesPsychologyEnergy (signal processing)Applied psychologyClinical psychologyMedicinePhysical therapyDisordered eatingEating disordersMathematics

Abstract

fetched live from OpenAlex

The Female Athlete Triad (Triad) and the more encompassing Relative Energy Deficiency in Sport (RED-S) are disorders caused by low energy availability (LEA). LEA is a state of insufficient energy intake by an athlete relative to their energy expenditure. Persistent LEA results in the deleterious consequences to health and performance that comprise RED-S. With respect to both the Triad and RED-S, researchers have called for more education of those involved with sport, particularly coaches, to help reduce the incidence of these disorders. Recent studies have shown that as few as 15% of coaches are aware of the Triad, with up to 89% unable to identify even one of its symptoms. RED-S is a more recently established concept such that coach knowledge regarding it has only begun to be assessed, but the results of these initial studies indicate similar trends as for the Triad. In this review, we synthesize research findings from 1986 to 2021 that pertains to LEA and RED-S, which coaches should know so they can better guide their athletes.

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 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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.100
Threshold uncertainty score0.506

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
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 head0.022
GPT teacher head0.289
Teacher spread0.267 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations34
Published2022
Admission routes1
Has abstractyes

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