Coupling of Eye, Finger, Elbow, and Shoulder Movements During Manual Aiming
Bibliographic record
Abstract
Temporal and spatial coupling of point of gaze (PG) and movements of the finger, elbow, and shoulder during a speeded aiming task were examined. Ten participants completed 40-cm aiming movements with the right arm, in a situation that allowed free movement of the eyes, head, arm, and trunk. On the majority of trials, a large initial saccade undershot the target slightly, and 1 or more smaller corrective saccades brought the eyes to the target position. The finger, elbow, and shoulder exhibited a similar pattern of undershooting their final positions, followed by small corrective movements. Eye movements usually preceded limb movements, and the eyes always arrived at the target well in advance of the finger. There was a clear temporal coupling between primary saccade completion and peak acceleration of the finger, elbow, and shoulder. The initiation of limb-segment movement usually occurred in a proximal-to-distal pattern. Increased variability in elbow and shoulder position as the movement progressed may have served to reduce variability in finger position. The spatial-temporal coupling of PG with the 3 limb segments was optimal for the pick up of visual information about the position of the finger and the target late in the movement.
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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".