“Ambient Fail” exception messages during breath testing of suspected impaired drivers using the Intoxilyzer® 5000C: a 10-year retrospective analysis
Bibliographic record
Abstract
A retrospective analysis of the incidence of the “Ambient Failed” exception message (AFM) generated by the Intoxilyzer® 5000C was conducted during breath testing of suspected impaired drivers over a 10-year period. The incidence of an AFM occurred in only 2.5% (n = 531) of the 21,016 drivers that were tested. Breath tests containing two AFMs (n = 21; approx. 0.1%) were even less frequent. There was no main effect in the incidence of AFMs attributable either to year (p = 0.83), location of testing (p = 0.72), or to use of different instruments (p = 0.59). Additionally, there was no evidence of alcohol, or other interfering substances, in the ambient conditions that may have falsely elevated either the calibration checks or the subject breath test results. The occurrence of an AFM was associated with elevated blood alcohol concentrations (BACs) compared with BACs from test records that did not contain an AFM. The mean (± standard deviation) BAC from breath test records that contained at least one AFM and from those that did not was 208 mg/100 mL (± 68) and 150 mg/100 mL (± 54), respectively. Ambient conditions needed to generate an AFM during breath testing are transient in nature and the triggering of an AFM is more likely to occur in subjects with elevated BACs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".