Coordination of Eye and Leg Movements During Visually Guided Stepping
Bibliographic record
Abstract
In the present study, 2 related hypotheses were tested: first, that vision is used in a feedforward control mode during precision stepping onto visual targets and, second, that the oculomotor and locomotor control centers interact to produce coordinated eye and leg movements during that task. Participants' (N = 4) eye movements and step cycle transition events were monitored while they performed a task requiring precise foot placement at every step onto irregularly placed stepping stones under conditions in which the availability of visual information was either restricted or intermittently removed altogether. Accurate saccades, followed by accurate steps, to the next footfall target were almost always made even when the information had been invisible for as long as 500 ms. Despite delays in footlift caused by the temporary removal (and subsequent reinstatement) of visual information, the mean interval between the start of the eye movement and the start of the swing toward a target did not vary significantly (p >.05). In contrast, the mean interval between saccade onset away from a target and a foot landing on that target (stance onset) did vary significantly (p <.05) under the different experimental conditions. Those results support the stated hypotheses.
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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 | 0.001 |
| 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) | 0.000 | 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".