A Comparison of Paired Calibration Check Results of<i>Alco-Sensor IV- RBT IV</i>and<i>Intoxilyzer® 5000 C</i>in Real Cases
Bibliographic record
Abstract
More than 1600 paired-control tests data obtained on Alco-Sensor IV—RBTIV and Intoxilyzer® 5000 C have been reviewed. A quasi-normal distribution around the target value of 100 mg/100 mL was observed. Moreover, not only are instruments accurate, but they are also stable. In sequences of tests in real cases, paired data comparison of first (CTRL1) and second (CTRL2) control results showed a difference (CTRL1—CTRL2) of zero in about one-third (⅓) of assays. The majority of cases (98.5%) were found to have a cumulative absolute difference of 3 mg/100 mL. In just one case, the difference between CTRL1 and CTRL2 was 10 mg/100 mL, the maximum acceptable in Quebec. Thus, although calibration checks of 95 to 105 mg/100 mL are acceptable, measurement uncertainty of these instruments should be considered well below 10 mg/100 mL in the great majority of cases.
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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 | 0.011 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".