The Effect of an Elevated Serum Methanol Concentration on the Intoxilyzer 5000C Results of a Drinking Driver
Bibliographic record
Abstract
A forty-year-old man was involved in a motor vehicle collision at 8:30 p.m. He was taken for medical assessment at a nearby hospital. Blood samples were collected at 10:41 p.m. and an alcohol screen was conducted on the serum. The serum alcohol (ethanol) concentration was found to be 346 milligrams in 100 millilitres of serum (mg/100 mL). In addition, an elevated serum methanol concentration of 4 mg/100 mL was also determined, which could be a biomarker of alcohol dependency or chronic, heavy consumption of alcohol. Two Intoxilyzer 5000C breath tests were conducted by the police at the hospital at 1:17 a.m. and 1:38 a.m., and the results were 240 mg/100 mL and 250 mg/100 mL, respectively. No Interferent message occurred and the Intoxilyzer results were not significantly increased by the presence of this high serum methanol concentration.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".