Mixed features and mixed states in psychiatry: from calculus to geometry
Bibliographic record
Abstract
Mixed features in psychiatry have historical, conceptual, nosological, and therapeutic implications. The historical perspective begins with Hippocrates and Aretaeus of Cappadocia and, after a hiatus, was followed by the writings of Heinroth, Falret, Kahlbaum, Weygandt, and Kraepelin. The conceptual motif consistent across Weygandt's and (his mentor) Kraepelin's model was combinatorial. Ostensibly, Weygandt and Kraepelin proposed a "calculus" approach to codifying nondementia praecox disorders, wherein the diagnosis was established by combining ratings along the 3 dimensions of mood, thought, and volition/activity (MTV). Uniform increases across all 3 domains defined mania; conversely, a decrease in each domain defined depression. Mixed states were the consequence of various combinations along MTV dimensions. Effectively, Weygandt and Kraepelin categorized the dimensions of psychopathology.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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 teacher head, 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".