Body Composition Adaptations Throughout an Elite Circus Student-Artist Training Season
Bibliographic record
Abstract
The purpose of this study was to perform a longitudinal assessment of body composition of circus student-artists in an elite 3-year college training program. Ninety-two student-artists participated (age = 20.39 ± 2.42 years; height = 170.01 ± 8.01 cm; mass = 66.48 ± 11.07 kg; 36% female and 64% male), representing 92% of the student population. Body composi- tion was assessed using multi-frequency bioelectrical impedance at four strategic time points throughout the training year to evaluate changes over the two semesters (September to December and January to April) and winter vacation (December to January). Workloads were subjectively assessed using ratings of perceived exer- tion (RPE). Averaged over the academic terms, fat mass was 11.5 ± 4.8%, muscle mass was 50.2 ± 3.4%, and body mass index was 22.9 ± 2.2. Males and females differed significantly across all absolute and relative body composition variables. Muscle mass increased (semester one, +1.0%, p < 0.001; semester two, +0.4%, p < 0.05) while fat mass decreased during each semester (semester one, -1.6%, p < 0.001; semester two, -0.6%, p < 0.05) co-varying with changes in RPE (semester one, +2.3, p < 0.05; semester two, +1.7, p < 0.05). During the winter vacation period, percent fat mass increased (males, +1.0%; females, +2.0%) and percent muscle mass decreased (males, -0.6%; females, -0.9%). Discipline-specific differences in body composition were also detected, and significant differences were observed between student-artists grouped by years in school. Over the training year, there was a positive adaptation for muscle and fat mass despite the negative adaptation experienced during the winter vacation period.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".