Intoxilyzer® 5000C or Alcotest® 7410 GLC as Headspace Analyser for Alcohol in Beverages
Bibliographic record
Abstract
A method of analyzing seized/suspected beverages for their alcohol content using the Intoxilyzer® 5000C or the Alcotest® 7410 GLC is reported. The accuracy of alcohol content on the labels of commercially sold beverages was also examined.Wines, beers and liquors (n = 21) bought from the open market were analyzed by headspace gas chromatography (GC). The data were compared with those obtained from using the Intoxilyzer® 5000C or Alcotest® 7410 GLC. With the latter two instruments, the headspace vapour of diluted beverages was blown into the calibrated instrument through the simulator. The results obtained by the latter two instruments were within ±6% of those obtained using the GC method.The labeled alcohol concentrations were within ±5% of the values measured by GC. They can, therefore, be used as the basis for blood alcohol concentration calculations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".