The Role of Oculomotor Information in the Learning of Sequential Aiming Movements
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
With their eyes initially on either the home, midline, or final end position, 30 participants practiced a 2-target aiming movement. After 120 acquisition trials, participants performed a retention test and were then transferred to each of the other 2 eye conditions. During acquisition, all groups improved over practice, but the home group showed the greatest improvement. The temporal improvement was most pronounced in the times spent after peak velocity. Retention and transfer tests indicated that participants performed best under eye-movement conditions that were the same as the 1 they had practiced in. There was also positive transfer of training between conditions in which the oculomotor information was similar. Thus, to optimize learning, one should practice under the same afferent and oculomotor conditions that will be required for the final performance.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 it