Lower-Right and Upper-Left Biases within Upper and Lower Visual Fields in a Circular Array Task
Bibliographic record
Abstract
Visuospatial performance varies along the horizontal and vertical dimensions, resulting in behavioral biases such as pseudoneglect. The interaction between the horizontal and vertical attentional biases was investigated using a novel circular array task capable of conveying relative brightness information across vertical and horizontal dimensions simultaneously. In a novel circular array task comprised of six discs, the grayscale gradient was disrupted by switching two grayscale values within the array. Leftward biases were observed in the lower visual fields and rightward biases in the upper visual fields. More importantly, the magnitude of bias within the upper/lower horizontal dimension altered depending on the relative position of the stimuli along horizontal and vertical axes within each dimension. Manipulating the upper-most and leftward discs yield stronger biases than manipulating rightward discs. Furthermore, stronger biases were observed during bottom and rightward disc manipulation. The upper-left and lower-right biases within the horizontal dimension indicate that the interactions between the horizontal and vertical biases may not rely simply on the dichotomy within the horizontal and vertical dimensions, but also on the relative spatial distribution of stimuli within these dimensions.
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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 | 0.002 |
| 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 | 0.001 |
| 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".