Primer Consenso Argentino sobre el manejo de la Esquizofrenia. Primera parte: Introducción, metodología de trabajo y generalidades
Bibliographic record
Abstract
The accumulated body of knowledge in the field of schizophrenia is vast yet often complex, fragmented, and, in some cases, inconsistent with certain practices that have been inadvertently perpetuated in psychiatric training over recent decades. In response to this gap, the Argentine Association of Biological Psychiatry (AAPB) initiated the development of the First Argentine Consensus on the Management of Schizophrenia, prepared by a multidisciplinary panel of national experts in the field. This article presents the first section of the consensus, which outlines the working methodology employed and reviews the current definition of schizophrenia, incorporating diagnostic criteria from both the DSM-5 and ICD-11. It also addresses the major unmet clinical needs in schizophrenia, summarizes recent neurobiological findings, and examines the environmental and psychosocial factors implicated in the onset and course of the disorder. Finally, the section emphasizes the importance of prevention and early intervention, highlighting the need for updated, evidence-based, and contextually adapted practices within the Argentine mental health system.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".