Moving Glass Patterns: Asymmetric Interaction between Motion and form
Bibliographic record
Abstract
The perceived motion direction of a moving Glass pattern is influenced by the orientation of the dot pairs (dipoles) that generate the pattern (Krekelberg et al, 2003 Nature 424 674-677; Ross, 2004 Vision Research 44 441-448). Here, we investigate how the motion vector and the dipole orientation of moving Glass patterns influence the perceived orientation of each. We employed 1 s movie presentations of sequences of linear Glass patterns, each consisting of 200 dot pairs. Signal pairs, aligned in a common orientation, moved in a common direction. The observer's task was to indicate either the perceived direction of motion, or the perceived dipole orientation of Glass patterns that consisted of either same-polarity dipoles, or opposite-polarity dipoles. Perceived orientation or motion direction was measured as a function of the angular difference between the orientation and the motion direction of the dipoles. We found that the apparent global direction of motion was attracted by approximately 4 degrees towards the dipole orientation for small (15 degrees, 23 degrees) angular differences between dipole motion-direction and dipole orientation, regardless of dipole polarity. However, under the same stimulus conditions, the apparent global orientation was much less affected by the direction of motion, suggesting that motion and form interact asymmetrically Global form influences global motion-direction perception more powerfully than global motion influences global form perception.
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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 | 0.002 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".