Bibliographic record
Abstract
Detection of a Gabor pattern is impaired in the presence of a similar pattern of orthogonal orientation, a phenomenon known as cross-orientation masking (XOM). Here we investigate the role of color in cross-orientation masking. We measured contrast detection thresholds to horizontally oriented Gabors overlaid by similar Gabors of a different orientation. Red-green chromatic masking was compared to achromatic masking for a wide range of spatial and temporal frequencies, orientations, and masks contrasts. We find that cross-orientation masking is significantly greater for chromatic than achromatic contrast. We also find it is invariant with the spatio-temporal conditions used, unlike achromatic cross-orientation masking that is known to have a spatio-temporal dependence (greatest for low spatial frequencies at high temporal frequencies). Furthermore, chromatic masking is isotropic (invariant across the orientation difference between test and mask), whereas the achromatic version of the masking effect displays orientation tuning, a phenomenon that was originally used to indicate the presence of orientationally selective mechanisms in human vision. We conclude that the P cell pathway or its projections can support cross-orientation masking. We propose distinct physiological origins for chromatic and achromatic masking, with a predominantly cortical site for chromatic masking in contrast to the M cell subcortical influences on achromatic masking suggested by previous studies.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".