Role of Chromaticity, Contrast, and Local Orientation Cues in the Perception of Density
Bibliographic record
Abstract
We compared the role of the red-green, blue-yellow, and luminance post-receptoral mechanisms in the perception of density. The task requires the comparison of densities between two stimuli composed of oriented bandpass elements, pseudo-randomly scattered across an area of constant size. The perception of density differences was measured by a temporal 2AFC procedure for all pairs of mechanisms and for four possible densities. We found that stimuli of identical physical densities are not perceived equally: there is a consistent bias in favour of blue-yellow stimuli which are perceived as significantly more dense than red-green and achromatic stimuli. We considered three factors that could have differentially affected the density perception of blue-yellow stimuli: an increase in the perceived size of the individual blue-yellow elements, a perceived contrast difference, and the presence of local orientation cues. We found that the increased perceived density of the blue-yellow stimuli occurred despite the fact that there was no increase in perceived size of the individual elements, and remained despite corrections for the two other factors. We conclude that the significant increase in perceived density for the blue-yellow mechanism is a global effect, associated with a perceived colour 'melting' of the elements in the array. Our data were fitted with the occupancy model of Allik and Tuulmets (1991, Perception & Psychophysics 49 303-314) and we found that blue-yellow stimuli have a greater 'occupancy' than red-green or achromatic stimuli.
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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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".