Bibliographic record
Abstract
Contingent on stereo compatibility, two images presented dichoptically can lead to either binocular integration, thus generating stable stereopsis, or interocular suppression that induces binocular rivalry with bistable perception that alternates between the two images. The relationship between binocular integration and interocular suppression concerns how our brain processes binocular inputs to form unified visual awareness but remains unclear. Here, a series of psychophysical experiments were conducted to address this question, revealing that these collaborative and competitive binocular interactions are interconnected and would mediate one another according to their strength. Specifically, Experiments 1a and 1b showed that the presence of binocular rivalry inhibited peripheral stereopsis, significantly elevating the stereo threshold, with higher elevation resulting from increasing rivalry contrast. Experiments 2a and 2b showed that existing stereopsis with increasing binocular disparity balanced the dynamics of peripheral binocular rivalry, rendering more equivalent eye dominance. Based on these interactions, we suggest that binocular integration and interocular suppression may mediate one another through an overlapping mechanism for regulating eye dominance, with strong stereo percepts tending to reduce eye dominance and strong rivalry tending to increase eye dominance.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".