Bibliographic record
Abstract
The classification of psychiatric illnesses was essentially based on stage theory, the idea that a given illness progressed from stage to stage. This was in contrast to the Kraepelinian scheme of classifying illnesses – with the exception of manic-depressive illness – on the basis of current phenomenology. According to the previous stage theories such as Zeller, Magnan and Griesinger, a major illness would typically begin with a mood picture (mania or melancholia), transition into psychosis (Verrücktheit, délire), then transition again in dementia. This illness course tended to be life-long, the order of the stages invariant (rarely was psychosis seen as the primary disorder, or did dementia yield to yet another stage). These concepts would be innovative in terms of the DSM system, which recognizes stage theory only in bipolar disorder. To clarify the nature of linear illness pictures (‘stage theory’) in a psychiatric presentation. To revive a traditional psychiatric concept of the linear illness entity (‘stage theory’) in the interest of improved diagnosis and treatment An analysis of the large past psychiatric literature in French, German, Italian, and English The illness courses of many past patients do seem to have unfolded in stages. Stage theory stemmed from senior clinicians of vast experience, whose ideas were are not entitled patronizingly to dismiss. The DSM system is now under assault and it may be time to reassess the usefulness of stage theory.
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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 | 0.031 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.017 |
| Scholarly communication | 0.009 | 0.031 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.010 | 0.024 |
| Insufficient payload (model declined to judge) | 0.012 | 0.008 |
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".