Seeing is remembering: Do deficits in closure affect visual memory recognition in schizophrenia?
Bibliographic record
Abstract
INTRODUCTION: Episodic memory is significantly impaired in people with schizophrenia. The precise cause of this impairment has yet to be determined, as the formation of episodic memories is dependent on other processes, some of which also show impairment in schizophrenia. One such process is closure, that is, the filling-in of missing information. Failure to close adequately incomplete stimuli may cause people with schizophrenia to store inadequate or piecemeal representations in memory. METHODS: Forty people with schizophrenia and 21 healthy comparison subjects participated in the study. The experiment was divided into six blocks, each of which involved both an encoding and a recognition phase. During the encoding phase, 20 figures were presented sequentially and participants had to determine whether each was symmetric or asymmetric. These figures were either complete or fragmented at three different levels. In subsequent recognition phase, 40 abstract figures (20 new and 20 old) were presented. All figures were complete in this phase. RESULTS: Memory performance of both groups was affected similarly by fragmentation, with an additional increase in performance afforded by a slight fragmentation for participants with schizophrenia. CONCLUSION: Slight fragmentation may have induced a perceptual difficulty that was mild enough to increase visual processing without compromising it. Closure was thus not involved in the episodic memory deficit of people 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 | 0.001 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".