The "Eyeballing" technique: an emerging and alerting trend of alcohol misuse.
Bibliographic record
Abstract
OBJECTIVE: Alternative methods of alcohol consumption have recently emerged among adolescents and young adults, including the alcohol "eyeballing", which consist in the direct pouring of alcoholic substances on the ocular surface epithelium. In a context of drug and behavioural addictions change, "eyeballing" can be seen as one of the latest and potentially highly risky new trends. We aimed to analyze the existing medical literature as well as online material on this emerging trend of alcohol misuse. MATERIALS AND METHODS: Literature on alcohol eyeballing was searched in PsychInfo and Pubmed databases. Results were integrated with a multilingual qualitative assessment of the database provided by The Global Public Health Intelligence Network (GPHIN) and of a range of websites, drug fora and other online resources between March 2013 and July 2013. RESULTS: Alcohol eyeballing is common among adolescents and young adults; substances with high alcohol content, typically vodka, are used for this practice across the EU and internationally. The need for a rapid/intense effect of alcohol, competitiveness, novelty seeking and avoidance of "alcoholic fetor" are the most frequently reported motivations of "eyeballers". Local effects of alcohol eyeballing include pain, burning, blurred vision, conjunctive injection, corneal ulcers or scarring, permanent vision damage and eventually blindness. CONCLUSIONS: Alcohol eyeballing represents a phenomenon with potential permanent adverse consequences, deserving the attention of families and healthcare providers. Health and other professionals should be informed about this alerting trend of misuse. Larger observational studies are warranted to estimate the prevalence, characterize the effects, and identify adequate forms of interventions for this emerging phenomenon.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".