Correction: Lithium Therapy in Old Age: Recommendations from a Delphi Survey
Bibliographic record
Abstract
Correction to: Lithium Therapy in Old Age: Recommendations from a Delphi Survey Pharmacopsychiatry 2023; 56(05): 188-196 DOI: 10.1055/a-2117-5200 Erratum Correction: Lithium Therapy in Old Age: Recommendations from a Delphi Survey Christl J, Müller-Oerlinghausen B, Bauer M et al. Lithium Therapy in Old Age: Recommendations from a Delphi Survey. Pharmacopsychiatry 2023 DOI: 10.1055/a-2117-5200 In the above-mentioned article, the 8th Citation, as well as the sentence which refers to it has been corrected. Correct is: “In a randomized controlled trial, Li was the more effective treatment option for therapy-resistant major depression compared to the monoamine oxidase inhibitor phenelzine. [8]” [8] Kok RM, Vink D, Heeren TJ et al. Lithium augmentation compared with phenelzine in treatment-resistant depression in the elderly: an open, randomized controlled trial. J Clin Psychiatry 2007; 68:1177-85 DOI: 10.4088/jcp.v68n080.3 This was corrected in the online version on August 29, 2023. Publication History Article published online: 30 August 2023 © 2023. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/). Georg Thieme Verlag Rüdigerstraße 14, 70469 Stuttgart, Germany
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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 | 0.025 | 0.242 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.073 | 0.045 |
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".