Exploration of vertical bias in perceptual completion of illusory contours: Threshold measures and response classification
Bibliographic record
Abstract
We investigated whether the perceptual completion of illusory contours exhibits a vertical bias (J. Pillow & N. Rubin, 2002). Experiments 1-3 measured completion with Pillow and Rubin's shape discrimination procedure, while including novel control conditions to determine if the results were related to perceptual completion per se. These experiments found no evidence for perceptual completion with stimuli used by Pillow and Rubin but did find completion with smaller stimuli that had larger support ratios. However, even when perceptual completion occurred, there was no evidence for a vertical bias in perceptual completion. Experiments 4-5 used the response classification method (B. L. Beard & A. Ahumada, 1998) to determine which local areas were related to illusory contour discrimination in central and peripheral vision. For central stimuli, there was a slight bias favoring completion of vertical contours, although the extent of the bias varied across participants. There was no vertical bias for peripheral stimuli. Overall, although subject to several important caveats, the results obtained with classification images (but not threshold measures) were consistent with the Pillow and Rubin's idea that perceptual completion is more difficult when it requires integrating visual features that are on different sides of the vertical meridian.
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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 | 0.001 |
| 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 | 0.000 |
| 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".