MétaCan
Menu
Back to cohort
Record W2999622054 · doi:10.1136/bjsports-2019-101926

#REDS (Relative Energy Deficiency in Sport): time for a revolution in sports culture and systems to improve athlete health and performance

2020· editorial· en· W2999622054 on OpenAlexaff
Kathryn E. Ackerman, Trent Stellingwerff, Kirsty J. Elliott‐Sale, Amy Baltzell, Mary Spencer Cain, Kara Goucher, Lauren Fleshman, Margo Mountjoy

Bibliographic record

VenueBritish Journal of Sports Medicine · 2020
Typeeditorial
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsMcMaster UniversityCanadian Sport Centre PacificUniversity of Victoria
Fundersnot available
KeywordsCoachingAthletesSubconsciousPsychologyEnergy (signal processing)MedicineApplied psychologySocial psychologyPhysical therapyAlternative medicinePsychotherapist

Abstract

fetched live from OpenAlex

Changing a sport system requires the appointment of new leaders or a grass roots cultural revolution. ‘I got caught in a system designed by and for men, which destroys the bodies of young girls,’ said Mary Cain as she cast light on her toxic coach/athlete relationship and exposed unhealthy coaching and nutrition practices. Her candour has inspired a social media movement calling for changes to women’s sport.1 In the following days, major news publications followed up with similar reports of athletic women being body shamed.2–4 It is time for a drastic paradigm change in women’s sport, coupled with education at all levels to improve the long-term health and athletic achievement of female athletes. The shift needs to include: 1. Raising awareness of the negative effects of chronic low energy availability (LEA) (calorie restriction) so athletes can make wise choices for their own long-term health. 2. Updating and developing best-practice protocols and safe standards for monitoring body composition/weight. 3. Eliminating toxic training environments featuring abusive body shaming. Overexercising or underfueling, occurring consciously or subconsciously, can cause Relative …

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.209
Threshold uncertainty score0.891

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.004
GPT teacher head0.225
Teacher spread0.221 · 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 designNot applicable
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

Citations94
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueBritish Journal of Sports MedicineSame topicMuscle metabolism and nutritionFrench-language works237,207