Bibliographic record
Abstract
The issue of Pharmacotherapy in Psychiatry and Neurology for the second half-year of 2022 contains one experimental paper, four review papers, and a case report.The experimental paper is about pharmacotherapy during the intervention of emergency medical teams (EMT) in people with mental disorders, based on two--year observation.Its first author is Łukasz Dudziński from the John Paul II Academy of Applied Sciences in Biała Podlaska.In the two-year period, EMT had 14,972 interventions in the investigated operational area (7,531 in the first year and 7,441 in the second year).The partial target of the analysis (patients with mental disorders) was achieved in 862 events (5.75% of the total).Most EMT interventions requiring the supply of drugs were associated with alcohol abuse and an acute reaction to stress.In 92 EMT interventions for mental disorders, pharmacological agents were administered, a total of 100 drugs, most often hydroxyzine (41%), diazepam (33%), captopril (6%), and multi-electrolyte fluid MEF500 (6%).The COVID-19 pandemic did not significantly affect the frequency of drug administration in EMT interventions.The aim of the first review paper, authored by Krzysztof Bogusz and Marcin Wojnar from the Department of Psychiatry, Medical University of Warsaw, is to review the current knowledge on brexpiprazole in the treatment of schizophrenia.Brexpiprazole is an antipsychotic drug that exhibits its effects mainly through partial agonism of D2 and D3 dopamine receptors and 5-HT1A serotonin receptors; it also has antagonistic Farmakoterapia w Psychiatrii i Neurologii 2022
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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 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.352 | 0.282 |
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".