Multicenter Evaluation of the Vitek 2 Anaerobe and <i>Corynebacterium</i> Identification Card
Bibliographic record
Abstract
The new anaerobe and Corynebacterium (ANC) identification card for Vitek 2 was compared with a 16S rRNA gene sequencing (16S) reference method for accuracy in the identification of corynebacteria and anaerobic species. Testing was performed on a Vitek 2 XL system with modified software at three clinical trial laboratories. Reproducibility was determined with nine ATCC quality control strains that were tested 20 times over a minimum of 10 days at all three sites. A challenge set of 50 well-characterized strains and 365 recent fresh and frozen clinical isolates were included in the study. The expected positive and negative biochemical well reactions were also evaluated for substrate reproducibility. All strains were tested with the ANC card, and clinical isolates were saved for 16S rRNA gene sequencing. All reproducibility tests yielded expected results within a 95% confidence interval, except for that with Corynebacterium striatum ATCC 6940, for which identification failed at one trial site. For the challenge isolates, there was 98% correct identification, 5% low discrimination, and 2% incorrect identification, and 0% were unidentified. For clinical strains, there was 95.1% correct identification, 4.9% low discrimination, and 4.6% incorrect identification, and 0.3% were unidentified. The 4.6% (17/365) of clinical isolates that were incorrectly identified consisted of 14 isolates that were correct at the genus level and three that were incorrect at the genus level. The new ANC card met all performance criteria within a 95% confidence interval compared to the identification performance by 16S rRNA gene sequencing.
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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 | 0.035 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 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".