EXPERTISE AND DISTANCE AS CONSTRAINTS ON COORDINATION STABILITY DURING A DISCRETE MULTI-ARTICULAR ACTION
Bibliographic record
Abstract
The purpose of this study was to identify how coordination variability of the shooting arm varied as a function of interacting task constraints of expertise and shooting distance. Skilled, intermediate and novice male basketball players (n=9 in each group) performed 30 shots from three distances (4.25, 5.25 and 6.25 metres). The dependent variables included shooting performance scores and measures of coordination variability in three joint couplings: wrist-elbow, elbow-shoulder and wrist-shoulder. A main effect for distance was observed for shooting performance, with a reduction in score occurring with increasing distance. Significant main effects for expertise were also apparent for shooting performance together with coordination variability for all three joint couplings. Regression analyses revealed significant, negative relationships between shooting performance and coordination variability for all three joint couplings irrespective of shooting distance. The findings corroborated extant data on changes in movement variability with practice, demonstrating how skilled performers assemble stable movement solutions to satisfy changing task constraints, in contrast to novices and intermediates.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".