Visual Guidance for Hand Advance but Not Hand Withdrawal in a Reach-to-Eat Task in Adult Humans: Reaching Is a Composite Movement
Bibliographic record
Abstract
Many animal species use reaching for food to place in the mouth (reach-to-eat) with a hand, and it may be a primitive movement. Although researchers (I. Q. Whishaw, 2005; A. N. Iwaniuk & I. Q. Whishaw, 2000; M. Gentiluci, I. Toni, S. Chieffi, & G. Pavesi, 1994) have described visual guidance of reaching in both normal and brain-injured human and nonhuman primates, researchers have not described the contribution of vision during advance of the limb to grasp food and during withdrawal of the limb with food to the mouth. To evaluate visual contributions, the authors monitored eye movements in young adults as they reached for food with and without vision. Participants visually engaged the target prior to the 1st hand movement and disengaged it as the food was grasped. Visual occlusion slowed limb advance and altered digit shaping but did not affect withdrawal. The dependence on visual control of advance but not withdrawal suggests that the reach-to-eat movement is a composite of 2 basic movements under visual and tactile/proprioceptive guidance, respectively.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 | 0.001 | 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".