[The Japanese version of the Calgary Depression Scale for Schizophrenics (JCDSS)].
Bibliographic record
Abstract
Depressive features are clearly recognized within the context of schizophrenia, and clarification of the comorbidity has important clinical implications particularly when choosing the best neuroleptics for treatment. However, in some cases, it is difficult to clearly distinguish between depressive symptoms, negative symptoms and extrapyramidal side-effects. Conventionally, the Zung's Self-Rating Depression Scale or Hamilton's Depression Rating Scale has been used as an evaluation scale of depressive symptoms. However, as these scales are designed for assessment of depression in non-psychotic populations, they do not necessarily distinguish depressed from non-depressed psychotic subjects. Recently, Addington et al. developed a new depression scale, the Calgary Depression Scale for Schizophrenics(CDSS), which was designed for the assessment of depression in schizophrenia. CDSS is a nine item structured interview scale, in which each item has a four point measure, each point anchored by descriptors. It has been tested, and it has been shown that there is no overlap with negative or extrapyramidal symptoms. Therefore, for its clinical application, we prepared the Japanese-language version(JCDSS).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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; 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".