Kanizsa's Shrinkage Illusion Produced by a Misapplied 3-D Corrective Mechanism
Bibliographic record
Abstract
In order to include the monocular areas from the left and the right eye in the cyclopean view, the visual system displaces the occluded elements which would result in a horizontal elongation of the shape but does not occur thanks to a correction mechanism which preserves the shape. We hypothesised that this mechanism causes Kanizsa's amodal shrinkage illusion (the apparent elongation of a partially occluded square) when it is incorrectly applied by the visual system to a two-dimensional stimulus. Four experiments tested this hypothesis: (i) one-eyed observers were less susceptible to the illusion than people with normal binocular vision because, for them, the correction for shape is unnecessary; (ii) the illusion was stronger with binocular than with monocular vision since binocularity induces the visual system to correct for the shape distortion; (iii) the illusion diminished when the stimulus was rotated 90 degrees given that displacement and compression are not required for vertical occlusion; (iv) the magnitude of the illusion was a function of the width of the occluder because, as previous research has shown, the edges of a partially occluded square are less displaced the farther they are from the edges of the occluder. The data from the four experiments support our hypothesis even though no condition was able to eliminate the illusion; other possible causes are discussed.
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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 | 0.003 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".