Analyses of Commercially Available Alcohol-Based Hand Rubs Formulated with Compliant and Non-Compliant Ethanol
Bibliographic record
Abstract
The COVID-19 pandemic led to panic-buying of alcohol-based hand rubs (ABHRs). In response, governmental agencies (e.g., Health Canada) permitted the sale of ABHRs formulated with “technical-grade” ethanol to alleviate the growing demand. Technical-grade ethanol contains elevated concentrations of impurities (e.g., acetaldehyde, etc.), which may exhibit dose-dependent toxicity. In this study, a rapid solvent extraction was employed to analyze gelled ABHRs via gas chromatography with flame ionization detection. In total, 26 liquid and 16 gelled ABHRs were analyzed for nine common impurities to determine compliance with Health Canada interim guidelines. Of 42 samples analyzed, 11 ABHRs appear to be non-compliant with interim Health Canada guidelines. Non-compliant ABHRs exhibited elevated concentrations of acetaldehyde, with a maximal concentration observed of 251 ± 10 µL L−1; 3.3× higher than currently permitted. Nonetheless, frequent testing of ABHRs should be routinely conducted to reduce the risk of consumer exposure to non-compliant ABHRs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".