Visual search performance among persons with schizophrenia as a function of target eccentricity.
Bibliographic record
Abstract
The current study investigated one possible mechanism of impaired visual attention among patients with schizophrenia: a reduced visual span. Visual span is the region of the visual field from which one can extract information during a single eye fixation. This study hypothesized that schizophrenia-related visual search impairment is mediated, in part, by a smaller visual span. To test this hypothesis, 23 patients with schizophrenia and 22 healthy controls completed a visual search task where the target was pseudorandomly presented at different distances from the center of the display. Response times were analyzed as a function of search condition (feature vs. conjunctive), display size, and target eccentricity. Consistent with previous reports, patient search times were more adversely affected as the number of search items increased in the conjunctive search condition. It was important however, that patients' conjunctive search times were also impacted to a greater degree by target eccentricity. Moreover, a significant impairment in patients' visual search performance was only evident when targets were more eccentric and their performance was more similar to healthy controls when the target was located closer to the center of the search display. These results support the hypothesis that a narrower visual span may underlie impaired visual search performance among patients with schizophrenia.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".