Bibliographic record
Abstract
Schizophrenia is a severe mental disorder marked by the presence of psychosis (delusions and hallucinations), disorganized behavior and language, emotional changes, and the presence of cognitive impairments and disability in everyday functioning. The disorder also occurs in several related variants, which include some of the features of the illness other than psychosis. Several features of schizophrenia and related conditions are important, particularly in the domains of cognitive deficits and disability. Recent innovations in the treatment of schizophrenia have focused on enhancing cognition. Whereas pharmacological interventions have met with limited success, cognitive remediation interventions have made considerable strides in the past decade. Like many other domains of research and treatment, advances in mapping the human genome and understanding the complexities of inheritance of behavioral traits have improved our understanding of schizophrenia. Although a complete profile of susceptibility genes is yet to be discovered, some genetic influences have been detected. The future of research and treatment in schizophrenia spectrum conditions will include advances in understanding the neuroscience of social behavior and social cognition, as well as developing combination therapies employing psychosocial/behavioral interventions and pharmacotherapy.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.075 | 0.017 |
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".