The contribution of metamemory deficits to schizophrenia.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A number of recent studies have demonstrated that individuals with schizophrenia display knowledge corruption; that is, they hold false information with strong conviction. This aberration in metamemory is thought to stem from poor memory accuracy in conjunction with impaired discrimination of correct and incorrect judgments in terms of confidence. Thirty-one participants with schizophrenia, along with 61 healthy control participants and 48 control participants with other psychiatric conditions, participated in a computerized source memory task. Whereas no differences in memory accuracy were observed between the group with schizophrenia and the group with other psychiatric diagnoses, knowledge corruption was specifically impaired in those with schizophrenia. Schizophrenia participants showed a significantly decreased confidence gap: They were more confident in errors and less confident in correct responses relative to those in the control groups. Knowledge corruption is theorized to be a potential risk factor for the emergence of delusions.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it