Unrecorded alcohol consumption in Russia: toxic denaturants and disinfectants pose additional risks
Bibliographic record
Abstract
In 2005, 30% of all alcohol consumption in Russia was unrecorded. This paper describes the chemical composition of unrecorded and low cost alcohol, including a toxicological evaluation. Alcohol products (n=22) from both recorded and unrecorded sources were obtained from three Russian cities (Saratov, Lipetsk and Irkutsk) and were chemically analyzed. Unrecorded alcohols included homemade samogons, medicinal alcohols and surrogate alcohols. Analysis included alcoholic strength, levels of volatile compounds (methanol, acetaldehyde, higher alcohols), ethyl carbamate, diethyl phthalate (DEP) and polyhexamethyleneguanidine hydrochloride (PHMG). Single samples showed contamination with DEP (275-1269 mg/l) and PHMG (515 mg/l) above levels of toxicological concern. Our detailed chemical analysis of Russian alcohols showed that the composition of vodka, samogon and medicinal alcohols generally did not raise major public health concerns other than for ethanol. It was shown, however, that concentration levels of DEP and PHMG in some surrogate alcohols make these samples unfit for human consumption as even moderate drinking would exceed acceptable daily intakes.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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 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".