Unrecorded alcohol consumption in Lithuania: a modelling study for 2000–2021
Bibliographic record
Abstract
The aim of the study was to estimate unrecorded alcohol consumption in Lithuania for the period 2000-2021 using an indirect method for modelling consumption based on official consumption data and indicators of alcohol-related harm. Methodology employed for estimating the unrecorded alcohol consumption was proposed by Norström and was based on the country's 2019 European Health Interview Survey and indicators of fully alcohol-attributable mortality. The proportion of unrecorded alcohol consumption was estimated as 8.30% (95% CI 7.7-8.9%) for 2019 in Lithuania. The estimated total (recorded and unrecorded) alcohol per capita consumption among individuals 15 years of age and older in 2019 was 12.2 L of pure alcohol, 1.01 (95% CI 0.94-1.09%) L of which is likely unrecorded. The lowest unrecorded alcohol level was estimated for 2009 and 2014, while 2018 had the highest level (i.e. 9.33% of total alcohol per capita consumption). Unrecorded alcohol consumption in Lithuania is likely to be modest when compared to recorded alcohol consumption, the latter of which still remains a major challenge to public health.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".