Research into alcohol-dependent persons in treatment during the COVID-19 pandemic. Part one – the mental health of patients
Bibliographic record
Abstract
Introduction:Although it is widely acknowledged that the COVID-19 pandemic has negatively affected the population's mental health, there has been little research into its effect on those with alcohol dependence, or those in addiction therapy during the period.The aim of the present study was to determine the level of mental performance of patients receiving treatment for alcohol dependence during the COVID-19 pandemic. StreszczenieWprowadzenie: Liczne badania wskazują, że pandemia COVID-19 wpływa negatywnie na zdrowie psychiczne populacji, jednak badań dotyczących osób uzależnionych od alkoholu przeprowadzono niewiele.Jednocześnie całkowicie pomijano osoby uczestniczące w tym okresie w terapii.Celem badań była odpowiedź na pytanie o poziom funkcjonowania psychicznego osób uzależnionych od alkoholu leczących się w okresie pandemii COVID-19.
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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 | 0.016 | 0.056 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.036 | 0.010 |
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".