Global shape aftereffects have a local substrate: A tilt aftereffect field
Bibliographic record
Abstract
Adaptation to prevailing stimuli is a ubiquitous property of the visual system that optimizes its dynamic range. The perceived difference in orientation of successively presented lines of similar orientation is exaggerated and the perceived shape of an object is influenced by previously experienced shapes. Change in perceived shape is assumed to arise through the adaptation of shape detectors. Here we consider an alternative: adaptation within a substrate of local oriented line detectors resulting in enhanced shape contrast in similar shapes. We show that the perceived shapes of a spatially coincident circle and Cartesian grid can be manipulated independently by adaptation to geometrically transformed copies of themselves. The same transformation was applied to the circle and the grid to create the adaptors; therefore, the specificity of the effects of adaptation demonstrates that the visual system adapts to the shape of objects rather than applying transformations to the reference frame of the visual field. The tilt aftereffect predicts local changes in perceived orientation, and fields of such local effects can often account for the global change in perceived shape of complex objects, including faces.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.007 | 0.001 |
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".