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Record W2972072336 · doi:10.21091/mppa.2019.3021

Sleep and Fatigue of Elite Circus Student-Artists During One Year of Training

2019· article· en· W2972072336 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMedical Problems of Performing Artists · 2019
Typearticle
Languageen
FieldMedicine
TopicMusicians’ Health and Performance
Canadian institutionsNational Circus School
Fundersnot available
KeywordsPerceived exertionPhysical therapyAthletesPsychologySleep qualitySleep onset latencySleep (system call)Rating of perceived exertionElite athletesEliteMental fatigueMedicinePhysical medicine and rehabilitationInsomniaApplied psychologyPsychiatryComputer science

Abstract

fetched live from OpenAlex

AIMS: The development of elite circus artists requires extensive technical and artistic training, as well as a commensurate level of physical preparation in readiness for a demanding professional career as a performance artist. While sport research has identified the importance of monitoring sleep and fatigue in athletes to optimize performance and to prevent illness and injury, not a single study of circus artists exists. This study provides a longitudinal examination of sleep and fatigue in elite circus student-artists. METHODS: 92 student-artists (60 male, 32 female) were analyzed at 4 strategic time points over a preparatory year. At each time point, sleep parameters (duration, quality and latency), ratings of perceived exertion (RPE), wakefulness, and fatigue were obtained using questionnaires. RESULTS: Student-artists attained an average nightly sleep of 8 hours, 27 minutes, exceeding the recommended durations for general populations and those self-reported in athletes. The majority of the artists also indicated acceptable sleep latency (87%) and quality (83%) scores. Sleep parameters remained consistent throughout the year despite significant variations in training load and fatigue. Sleep parameters were not substantial predictors of overall fatigue. Fatigue covaried with yearly variation in sessional training loads. CONCLUSIONS: Although improvement in sleep could be postulated as a means to mitigate fatigue, it is likely that strategies aimed at optimizing the loading profile and additional recovery techniques be a first line approach.

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.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.179
Threshold uncertainty score0.614

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)0.0010.000

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 head0.032
GPT teacher head0.302
Teacher spread0.270 · 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