Picture Surface Illusion: Small Effects on a Major Axis
Bibliographic record
Abstract
Perception of 2-D ellipses on a picture surface is inaccurate-if the ellipses depict circles that are tilted in 3-D, receding from the viewer (Hammad, Kennedy, Juricevic, & Rajani, 2008a, Perception, 37, 504-510). Notably, the minor axis of the ellipse is seen as larger than is true. This illusory effect could be due to the simultaneous presence of optical information for the 2-D ellipse and optical information for the 3-D tilted circle. The optical information for the circle may bias vision's use of the optical information for the ellipse. This theory predicts that illusory effects should occur on the major axis as well as the minor axis; but, we argue, the major axis effect should be smaller than the minor axis effect. We confirm the prediction. Observers looked at target ellipses depicting tops of tilted cylinders. In one experiment observers chose a match for the target from choice sets of seven 2-D ellipses. In the second, observers used the method of adjustment. Both axes were overestimated, the minor axis more than the major, as the theory suggested. We point out that the relative size of the effects matters to the theory, and so the small effect counts for a lot.
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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 | 0.002 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".