Bibliographic record
Abstract
The purpose of this study was to identify those mechanical determinants or their trends that distinguished a gymnast's best performance of the double back salto dismount on parallel bars from those judged to be inferior. Dismounts, in the tucked position, by nine Canadian gymnasts were analysed. Unique to this study was the inclusive analysis of multiple performances of the same skill by these athletes. It was felt that within-subject comparisons would reveal the kinematic variables on which the gymnast may focus in order to achieve their best performances. A non-parametric median sign test was used to compare mechanical variables, within subjects, between the dismount judged the best and those dismounts awarded a lower score. Three judges judged each dismount. In comparison to poorer performances of the dismount, statistical analyses revealed that athlete's best performances were characterised by (1) a higher release point, more vertical velocity yet with less angular momentum at take-off, (2) greater height, with a tighter and earlier tuck position during the flight phase, and (3) a greater range of motion and a more compact squat position at landing (all p's < .06).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.023 | 0.006 |
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".