Tercer Consenso Argentino sobre el manejo de los Trastornos Bipolares. Primera Parte: introducción, método de trabajo y generalidades
Bibliographic record
Abstract
The Third Argentine Consensus on the management of bipolar disorders (TB) is an initiative of the Argentine Association of Biological Psychiatry (AAPB). As a reference document, this consensus pursues two main objectives: on the one hand, to summarize and systematize the best available evidence on the comprehensive management of this pathology; on the other, to provide a useful, up-to-date instrument for psychiatrists, multidisciplinary teams dedicated to mental health, and government agencies. During a period of approximately six months of work -that is, from May to October 2022- a committee of experts made up of 18 professionals and representatives of the three most important Psychiatry and Mental Health associations in Argentina (that is, the AAPB, the Argentine Association of Psychiatrists, AAP, and the Association of Argentine Psychiatrists, APSA) have focused on updating the information regarding TB. Finally, this document was prepared as a result of an exhaustive review of the bibliography published to date, which was strategically divided into three parts: the first deals with the generalities of TB; the second deals with the comprehensive treatment of the pathology; finally, the third analyzes TB in the context of special situations.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".