Tetracycline-resistant coliforms in the effluent of the main sewage treatment plant in Hamilton, Ontario — do they have a common ancestral strain?
Bibliographic record
Abstract
Sewage, a major source of bacterial contamination of the environment, can be an important health hazard. The presence of antibiotic-resistant bacteria in sewage can exacerbate this problem. The sources of antibiotic-resistant bacteria in sewage are, for this reason, worth identifying and addressing. The bacterial flora in the effluent of the Woodward Avenue Wastewater Treatment Plant (WAWTP) in Hamilton, Ontario, Canada, contains many antibiotic-resistant coliforms. Here we ask, are the antibiotic resistance genes in the coliforms in the effluent of WAWTP descended from a recent common ancestor strain? If so, the source could be identified and eliminated. If, on the other hand, the antibiotic resistance genes in the bacterial flora of the WAWTP have more than one origin, identification and elimination of the source(s) could be difficult. There was considerable diversity of antibiotic resistance patterns and antibiotic resistance genes among the effluent and influent coliform isolates of the WAWTP, suggesting multiple genetic ancestry. The patterns of horizontal transmissibility and sequence differences in the genes tetA and tetE among these coliform isolates also suggest that they have no one predominant ancestral strain. Using the same logic, the evidence presented here is not compatible with a single ancestral origin of the antibiotic resistance genes in the isolates described herein.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".