Using Treatment Response to Subtype Schizophrenia: Proposal for a New Paradigm in Classification
Bibliographic record
Abstract
Phenomenology and Diagnosis The treatment and classification of schizophrenia continue to represent an enormous challenge. Phenomenology and outcome remain the basis of present classification systems although both are heterogeneous and overlap with other psychiatric disorders.1,2 Efforts are in place for change; eg, the Working Group on Classification of Psychotic Disorders for ICD-11 has recommended omitting the traditional subtypes such as paranoid, catatonic, etc., in accordance with DSM-5, the major argument being lack of clinical utility in routine clinical practice.3,4 We believe the changes advocated do not go far enough because classification still relies heavily on symptom clusters. Adding severity and course specifiers, as is the case in the ICD-11 draft, or multiple dimensions (DSM-V) may represent more of a challenge than benefit for clinicians in their busy daily practices. Moreover, the reliability and predictive validity of these specifiers and domains are not well established and, possibly, not substantively better than the subtypes that have been abandoned.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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; both teacher heads agree on what is shown here.
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".