Dichoptic color saturation mixture: Binocular luminance contrast promotes perceptual averaging
Bibliographic record
Abstract
We demonstrate a new type of interaction between suprathreshold color (chromatic) and luminance contrast in the context of binocular vision. When two isoluminant colored disks of identical hue but different saturations are presented to different eyes, the apparent saturation of the resulting "dichoptic" mix is close to that of the more saturated patch if presented binocularly. This result is commensurate with previous findings using luminance contrast and is close to the scenario termed "winner-take-all." However, when binocularly matched luminance contrast is added to the dichoptic saturation mixture, the apparent saturation of the mixture shifts away from winner-take-all towards the average of the two dichoptic saturations. The likely cause of this effect is that the matched luminance contrasts reduce the interocular suppression between the unmatched color saturations. We suggest that the presence of binocularly matched luminance contrast promotes the interpretation that the dichoptic color saturations, even though unmatched, nevertheless originate from the same object. We term this idea the "object commonality" hypothesis.
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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 | 0.001 |
| 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 | 0.001 |
| 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".