Stereoscopic slant contrast revisited
Bibliographic record
Abstract
The perceived slant (or inclination) of a slanted stereoscopic surface is affected by a surrounding stereo-slanted surface. Previous studies have shown that the effect is generally contrasting, that is the perceived slant of the test stereo-surface is shifted away from that of the surrounding stereo-surface. However previous studies have not established whether a surrounding stereo surface affects test surfaces slanted in the opposite slant direction, and have not measured the mutual contrasting effect between test and surround in order to measure their perceived angular difference. Using an adjustable matching slanted surface in a two-interval-forced-choice procedure, observers measured the perceived slant of both a central test as well as its surrounding surface for a range of combinations of test and surround slants. For each combination of test and surround slant two measures were calculated: (1) the perceived slant difference between the test and surround when the two were presented in isolation and (2) the perceived slant difference between the test and surround when the two were presented in combination, i.e. when affecting each other. The difference between these two measures is termed here the mutual contrasting effect, or MCE. MCEs were plotted as a function of surround slant; as the test-surround slant difference increased from zero, there was a sharp rise in MCEs followed by various degrees of decline at larger test-surround slant differences. Importantly, MCEs were consistently observed with opposite signs of test and surround slant. Our findings suggest that positive and negative stereoscopic slants are encoded by a single bipolar mechanism, one subject to mutual inhibitory interactions between neighboring stereo-slanted surfaces that rapidly rise and gradually decline with the angular difference between test and surround.
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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 | 0.003 |
| 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 | 0.001 |
| 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".