Visual Feedback Use during a Back Tuck Somersault: Evidence for Optimal Visual Feedback Utilization
Bibliographic record
Abstract
We aimed to determine if visual feedback use during aerial skills is more efficient at low angular head velocity (AHV; i.e., <350 deg/s) than at high AHV. Twelve experienced female acrobats performed 20 back tuck somersaults under four experimental conditions: full-vision (FV), vision at AHV below 350 deg/s (VBelow), vision at AHV above 350 deg/s (VAbove), and no-vision (NV). AHV was calculated in real time, and liquid crystal goggles were used to manipulate vision. Two gymnastics judges scored landing stability using a four-point scale. All vision conditions that allowed some vision yielded significantly better landing scores than in the NV condition. Furthermore, a nonparametric test revealed that VBelow yielded a better performance ranking than the FV condition. We conclude that visual feedback during a back tuck somersault is used for landing stability at all angular head velocities, but optimal feedback use occurs when there is retinal stability.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".