Horizontal/Vertical Differences in Range and Upper/Lower Visual Field Differences in the Midpoints of Sensory Fusion Limits of Oriented Lines
Bibliographic record
Abstract
O'Shea and Crassini (1982, Perception & Psychophysics 32 195-196) demonstrated that fusion persists for vertical lines with an orientation disparity of 8 degrees, but diplopia is experienced in simultaneously presented horizontal lines with the same disparity. They concluded that the neural fusion process fuses larger horizontal disparities than vertical disparities. Kertesz criticised their demonstration because it did not quantify the possible motor component associated with fusing their counter-rotated images. Krekling and Blika argued that the demonstrated anisotropy is due to a disparity bias in the visual system, owing to the temporalward tilt of corresponding vertical meridians. We addressed these criticisms with a novel stimulus and presentation protocol, that rendered compensatory cyclovergence eye movements unlikely and explored a wide range of orientation disparities. We confirmed O'Shea and Crassini's vertical/horizontal anisotropy in orientation fusion limits. In addition, our measurements of vertical lines showed that the distributions of fused responses as a function of orientation disparity in the upper and lower visual fields were shifted relative to each other. Therefore, the distributions of fusible orientation disparities are wider for vertical lines than horizontal lines and are relatively shifted as predicted if the fusional range is centred around the vertical horopter.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".