Is performance on probed serial recall tasks in schizophrenia related to duration of Attentional Blink?
Bibliographic record
Abstract
Schizophrenia is associated with a deficit in working memory, with the degree of working memory impairment related to the level of social and occupational functioning. This study tests the hypothesis that the working memory deficits in individuals with schizophrenia can be explained by slow processing of visual stimuli, as measured by the attentional blink (AB) task. Individuals with schizophrenia (SC) and controls (HC) were recruited from an early intervention service for psychosis and the local community. Data from 16 SC (11M/5F, mean = 26.4 yo) and 20 age-matched HC (11M/9F, mean = 25.8 yo) were analyzed. Each subject performed an AB task to determine their AB duration, defined as the lag to reach their plateau performance (ltpp). As expected, mean AB duration in the SC group (575 ms) was significantly slower than HC (460 ms; p = 0.007). Recall accuracy of the SC group on a working memory task, a 6-item probed serial recall task (PSR), was reduced compared to the HC group at a standard interstimulus interval (ISI) (p = 0.002). When the individual's AB duration was then used to adjust the ISI on the PSR task to three relative ISI rates (Slow (2 × ltpp), Medium (ltpp) and Fast (1/2 × ltpp)), performance on the PSR task was affected by group, position and ISI and qualified by an ISI ∗ position (p = 0.001) and a trend to a triple interaction (p = 0.054). There was main effect of group at all ISIs, but group ∗ position interaction only at Slow ISI (p = 0.01). Our interpretation of the results is that absolute ISI, rather than ISI relative to AB duration, affected performance.
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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 | 0.003 |
| 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 | 0.001 | 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".