Triangular backgrounds shift the bias of line bisection performance in hemispatial neglect
Bibliographic record
Abstract
OBJECTIVE: Patients with left neglect on line bisection show normal implicit sensitivity to manipulations of both the stimulus and the visual background. Three experiments were designed to define this sensitivity more exactly. METHODS: Normal controls and patients with left neglect performed a series of horizontal line bisection tasks. Independent variables were the configurations of the backgrounds for the line-rectangle, square, circle, left and right pointing isosceles triangles-and whether the background was the shape of the piece of paper or an outline drawn on a standard piece of paper. In a separate experiment different components of the triangle were outlined on a piece of paper. Deviation from true midpoint was calculated. RESULTS: Simply placing the target lines in a symmetric background such as a square or circle did not reliably reduce neglect. A triangle asymmetric in the horizontal plane caused a shift in bisection away from the triangle's vertex. With right pointing triangles the perceived midpoint shifted to the left of true centre (crossed over). The effects of the triangles were comparable in the patients and the controls when controlled for baseline bisection bias. The critical components of the triangles were the angular legs. This effect of background was not influenced by lesion site or by hemianopia. CONCLUSIONS: Patients with left visual neglect remain sensitive to covert manipulations of the visual background that implicitly shift the perceived midpoint of a horizontal line. This effect is strong enough to eliminate neglect on a bisection task. The mechanism of this effect is expressed through preattentive visual capacities.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".