Three-Dimensional Manual Responses to Unexpected Target Perturbations During Rapid Aiming
Bibliographic record
Abstract
The authors examined the execution of rapid aiming movements to targets that changed size and position. Participants viewed a medium-size target during movement preparation. The target became smaller or larger at movement initiation on size perturbation trials. The target moved closer or farther away from the home position on amplitude perturbation trials. The authors examined-in addition to several performance measures-the volume of 3-dimensional ellipsoids to quantify between-trials variability. In the size protocol, men executed movements in a similar manner irrespective of condition. In contrast, women exhibited less variability when target size increased. In the amplitude protocol, men moved inconsistently in the latter portion of the trajectory when targets became proximal. Men also failed to adjust for the perturbation on several trials. In comparison, women were more variable in the initial portions of the trajectory when the target became distal. Although men and women performed their movements in a similar duration, the trajectory and error analyses indicated different behaviors. Specifically, women made more rapid and efficient adjustments to their trajectories on the basis of concurrent visual information. In contrast, men executed movements on the basis of the visual information initially presented and then made adjustments, rather than gathering visual information and executing adjustments throughout the trajectory.
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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 | 0.005 |
| 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) | 0.001 | 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".