Monocular and Binocular Vision in the Control of Goal-Directed Movement
Bibliographic record
Abstract
In the present research the authors examined the time course of binocular integration in goal-directed aiming and grasping. With liquid-crystal goggles, the authors manipulated vision independently to the right and left eyes of 10 students during movement preparation and movement execution. Contrary to earlier findings reported in catching experiments (I. Olivier, D. J. Weeks, K. L. Ricker, J. Lyons, & D. Elliott, 1998), neither a temporal nor a spatial binocular advantage was obtained in 1 grasping and 2 aiming studies. That result suggests that, at least in some circumstances, monocular vision is sufficient for the precise control of limb movements. In a final aiming experiment involving 3-dimensional spatial variability and no trial-to-trial visual feedback about performance, binocular vision was associated with greater spatial accuracy. Binocular superiority appeared to be most pronounced when participants were unable to adjust their limb control strategy or procedure on the basis of terminal feedback about performance.
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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 | 0.001 |
| 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".