Integration of Intermittent Visual Samples Over Time and Between the Eyes
Why this work is in the frame
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Bibliographic record
Abstract
The authors investigated the integration of alternate disparate monocular inputs for binocular perception in 1-handed catching experiments (N = 14, 32, 22, and 15 participants, respectively in Experiments 1-4). They varied the no-vision interval between alternate monocular samples to measure catching performance, and they compared the alternating monocular conditions with binocular and monocular conditions with equal no-vision intervals. They found no evidence of a binocular advantage for one-handed catching in the alternating monocular conditions. Performance in monocular and alternating monocular conditions did not differ across no-vision intervals ranging from 0-80 ms and was particularly worse than performance in binocular viewing conditions when the no-vision interval was 40 ms or more. The authors argue that the dissimilarity between disparate monocular inputs created by the approaching object limited the integration of those inputs and subsequent binocular perception.
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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 | 0.000 | 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