Reach corrections toward moving objects are faster than reach corrections toward jumping targets
Bibliographic record
Abstract
Abstract Visually guided reaching is a common motor behavior that engages subcortical circuits to mediate rapid corrections. These circuits help us successfully grasp objects we see, even if those objects move during the reach. Although these neural mechanisms have evolved for interaction with the physical world, they are almost always studied in the context of reaching toward virtual targets displayed on a computer or projection screen. Virtual targets are unrealistic both because they cannot be physically grasped and because they generally move by “jumping” from one place to another instantaneously. Recent work has indicated that various aspects of “real” visual stimuli, including proximity and graspability, elicit distinct neural activity. In this study, we instructed participants to perform rapid reaches to physical objects. On some trials, these objects either moved realistically (continuously from one position to another) or unrealistically (jumping instantaneously to an equivalent position). Participants were consistently faster in correcting their reach trajectories when the object moved continuously.
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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 | 0.007 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".