Bibliographic record
Abstract
Ogle's induced-size effect refers to the percept of slant elicited by a difference in vertical size between the left and right half images of a stereoscopic display. The effect is not readily predicted by the geometry of the situation and has been of considerable interest in the stereoscopic literature. Rogers and Koenderink (Nature, 322: 62–63) demonstrated that modulation of the vertical size of a monocular image during lateral head motion produces the impression of a surface slanted in depth — a motion-parallax analogue of the induced-size effect. We investigated motion parallax analogues of the induced-size and induced-shear effects further and compared them with the corresponding stereoscopic versions. During lateral head motion or with binocular stereopsis, vertical-shear and vertical-size transformations produced ‘induced effects’ of apparent inclination and slant that are not predicted geometrically. With vertical head motion, horizontal-shear and horizontal-size transformations produced similar analogues of the disparity induced effects. Typically, the induced effects were opposite in direction and slightly smaller than the geometric effects. For both stereopsis and motion parallax, relative slant and inclination were more pronounced when the stimulus contained discontinuities in disparity/velocity gradient than for continuous disparity/flow fields. The results have important implications for the processing of disparity and optic flow fields.
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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) | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".