Solving the Correspondence Problem within the Ternus Display: The Differential-Activation Theory
Bibliographic record
Abstract
The Ternus display produces a bistable illusion of motion: at very short interstimulus intervals (ISIs; < 30 ms) observers perceive element motion while at longer ISIs (> 30 ms) observers perceive group motion. In experiment 1, however, we find that, when the Ternus display's ISI contains an occluding box, group motion is mostly eliminated. These results do not fit the predictions made by the short-range/long-range two-process theory [Braddick and Adlard, 1978, in Visual Psychophysics and Psychology (New York: Academic Press)]. We propose that the differential-activation theory (Gilroy et al, 2001 Perception & Psychophysics 63 847-861) accounts for our results. We then extend the differential-activation theory as an explanatory mechanism for the Ternus display in experiment 2 by selectively placing an occluder over the first, second, or third Ternus display element. As predicted by the differential-activation theory, the occlusion of the far-left element produced a normal distribution of group motion increasing with ISI, while the occlusion of the other two elements produced an illusion of occluded elements remaining stationary throughout the display. Furthermore, as predicted by the differential-activation theory, each moving element was assigned to its nearest neighbour, producing, in the case of second and third element occlusion, a novel Ternus display motion illusion where only two out of three elements are perceived as moving.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".