Analytical limits of three β-glucosidase-based commercial culture methods used in environmental microbiology, to detect enterococci
Bibliographic record
Abstract
The enzyme-based test methods Enterolert, Chromocult Enterococci agar, and mEI agar, used to assess water quality through the detection Enterococcus spp., have been compared in terms of their analytical specificity and their ability to detect various enterococcal strains. To achieve this goal, we have tested 110 different non-enterococcal bacterial strains and 101 strains of Enterococcus spp. isolated from diverse origins. The results obtained showed that 69 (68.3%), 84 (83.2%), and 89 (88.1%) of the 101 enterococcal strains tested respectively yielded a positive signal with Enterolert, mEI, and Chromocult Enterococci. Regarding the specificity, none of the non-Enterococcus spp. strains tested were detectable by any of the three culture methods, except for Granulicatella adiacens which turned out positive on Chromocult Enterococci. The results of this study showed that, based on our collection of strains, the Enterolert test method detected less enterococcal strains than the two other methods.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".