Distinguishing Bipolar Depression, Major Depression, and Schizophrenia With the MMPI-2 Clinical and Content Scales
Why this work is in the frame
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Bibliographic record
Abstract
Clinical and content scales from the MMPI-2 (Butcher, Dahlstrom, Graham, Tellegen, & Kaemmer, 1989) were used to examine the capacity of these scales to assist in the differential diagnosis of a sample of 212 psychiatric patients-137 with major depression; 43 with schizophrenia; and 32 with bipolar disorder, depressed state. Consistent with the previous literature, the clinical scales Depression (D), and Schizophrenia (Sc), and the content scales Depression (DEP), and Low Self-Esteem (LSE) best distinguished major depression from schizophrenia; the content scale DEP proved to be the most powerful predictor in distinguishing bipolar depression from schizophrenia. No clinical or content scale proved to be effective in distinguishing patients with bipolar depression from patients with major depression. In general, the content scales outperformed the clinical scales.
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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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it