No correlation between interocular delay and stereosensitvity in healthy adults
Bibliographic record
Abstract
The perception of depth and objects in space hinges on the collaborative information received from both eyes in the visual system. Stereoscopic acuity, defining the smallest perceivable disparity between the 2 eyes, typically ranges from 30 to 60 seconds of arc in healthy individuals. To perceive stereoscopic vision accurately, the information from the 2 eyes must be received synchronously by the visual brain. This study aimed to uncover the correlation between interocular delay and stereoscopic vision quality in healthy vision. We measured and compared stereosensitivity and interocular delay in 29 healthy adults. Interocular delay was measured using a novel continuous psychophysics paradigm (Burge and Cormack, BioRxiv, 2020). Stereosensitivity was measured using a novel stereotest (Tittes et al., Vision Research, 2019) and the standard Randot Stereotest in 29 healthy adults. Our results suggest that there is no correlation between stereoacuity and interocular delay in our healthy population. Although interocular asynchrony is associated with several binocular vision disorders, we did not observe a correlation between interocular delay and stereoacuity in our healthy population. It is worth noting that, in both of our tests, stereosensitivity was measured using an unlimited presentation time. It is possible that interocular delay has more impact when using shorter presentation times.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".