Examining the effects of two factors on working memory maintenance of bound information in schizophrenia
Bibliographic record
Abstract
Integrating information in space and time is a central feature of episodic memory. Although disturbance of the binding processes in episodic memory is well established in patients with schizophrenia, data on working memory (WM) remain discrepant. In a change detection procedure, two target displays of pairs of letters located in cells of grid were successively presented. Participants attempted to detect changes in binding information (i.e., recombination of studied features) or feature information (i.e., a novel letter and/or a novel spatial location). Recombinations consisted of features belonging to the same display (intradisplay) or different displays (interdisplays). Results showed that patients demonstrated overall lower performance, with no specific deficit for recognizing bound information or feature information. In addition, patients did not demonstrate deficits for interdisplay recombinations or intradisplay recombinations. Patients' ability to remember temporal occurrence of stimuli was not affected. Together, these results suggest that in patients with schizophrenia, binding processes in WM are not specifically disturbed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".