Comparative analysis of classical and molecular microbiology methods for the detection of Escherichia coli and Enterococcus spp. in well water
Bibliographic record
Abstract
The microbiological quality of 165 1 litre well water samples collected in the Québec City region was assessed by culture-based methods (mFC agar, Chromocult coliform agar, Colilert(®), MI agar, Chromocult enterococci, Enterolert™, and mEI agar) and by a molecular microbiology strategy, dubbed CRENAME-rtPCR, developed for the detection of Escherichia coli, Enterococcus spp., Enterococcus faecalis/faecium, and Bacillus atrophaeus subsp. globigii. In these drinking water samples, approved culture-based methods detected E. coli at rates varying from 1.8 to 3.6% and Enterococcus spp. at rates varying from 3.0 to 11.5%, while the molecular microbiology approach for E. coli was found to be as efficient, detecting contamination in 3.0% of samples. In contrast, CRENAME-rtPCR detected Enterococcus spp. in 27.9% of samples while the E. faecalis/faecium molecular assay did not uncover a single contaminated sample, thereby revealing a discrepancy in the coverage of waterborne enterococcal species detected by classical and molecular microbiology methods. The validation of the CRENAME-E. coli rtPCR test as a new tool to assess the quality of drinking water will require larger scale studies elaborated to demonstrate its equivalence to approved methods.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".