Patient Functioning, Life Engagement, and Treatment Goals in Major Depressive Disorder
Bibliographic record
Abstract
See more Academic Highlights in this series: Part 1 | Part 2 This Academic Highlights section of The Journal of Clinical Psychiatry presents the highlights of the virtual roundtable “Patient Functioning and Life Engagement: Unmet Needs in MDD and Schizophrenia,” which was held May 10, 2022. The roundtable was chaired by Christoph U. Correll, MD, Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York, and Charité Universitätsmedizin, Berlin, Germany. The faculty were Zahinoor Ismail, MD, Department of Psychiatry, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada; Roger S. McIntyre, MD, Mood Disorder Psychopharmacology Unit, University Health Network, Department of Psychiatry, University of Toronto; Institute of Medical Science, University of Toronto; and Departments of Psychiatry and Pharmacology, University of Toronto, Toronto, Ontario, Canada; Roueen Rafeyan, MD, Department of Psychiatry, Feinberg School of Medicine, Northwestern University, Chicago, Illinois; and Michael E. Thase, MD, Department of Psychiatry, Perelman School of Medicine of the University of Pennsylvania, and the Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania. Financial disclosures: Please refer to the first Academic Highlights in this series: Correll CU, Ismail Z, McIntyre RS, et al. Patient functioning and life engagement: unmet needs in major depressive disorder and schizophrenia. J Clin Psychiatry. 2022;83(4):LU21112AH1 (https://doi.org/10.4088/JCP.LU21112AH1) This evidence-based peer-reviewed Academic Highlights was prepared by Healthcare Global Village, Inc. Financial support for preparation and dissemination of this Academic Highlights was provided by H. Lundbeck A/S and Otsuka Product Development and Commercialization. The faculty acknowledges Sarah Brownd, MA, ELS, for editorial assistance in developing the manuscript. The opinions expressed herein are those of the faculty and do not necessarily reflect the views of Healthcare Global Village, Inc., the publisher, or the commercial supporters. This article is distributed by H. Lundbeck A/S and Otsuka Product Development and Commercialization for educational purposes only.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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".