A Comparison of Methods for Measuring Interocular Delays
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Bibliographic record
Abstract
Many everyday tasks rely on binocular vision, which is impaired in individuals with amblyopia. Impairments in visual-spatial processing normally characterize amblyopia, but previous work has shown deficits in temporal processing as well, including processing delays in the amblyopic eye. Many techniques have been developed to measure interocular timing delays behaviourally by showing different images to the two eyes and recording participant responses. However, agreement between these measures has not been previously investigated. We compared four different assessment measures in normally-sighted observers: depth-based judgments (using the Pulfrich effect), interocular flicker integration, reaction time to monocular targets, and interocular temporal order judgments. Stimuli were presented using a high-speed projector with passive polarized filters (240 Hz per eye), enabling precise temporal control for dichoptic presentation. We also included a measure of sensory eye dominance to determine how eye dominance is related to each of the timing-based measurements. Pairwise comparisons of temporal delays measured across methods showed that the best-correlated pair of measures was between interocular flicker integration and temporal order judgements (r = 0.50). For each measure, we additionally calculated the average correlation between it and the remaining three measures. The Pulfrich effect was the best-correlated measure for examining timing delays between the eyes (Fisher Z = 0.24). In contrast, the measure that was least correlated with the other three measures was reaction time (Fisher Z = 0.09). Eye dominance was not correlated with the four temporal delay measures (Fisher Z = -0.01). Together, these results suggest that methods that rely on binocular integration are more reliable than monocular measurements. This highlights the importance of selecting appropriate tools for measuring interocular delays, and that suggests that combining specific methods may better characterize temporal delays seen in visual impairments.
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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 | 0.004 | 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 it