Potential of <i>Enterococcus faecalis</i> as a Human Fecal Indicator for Microbial Source Tracking
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Regulatory agencies are interested in a fecal indicator bacterium with a host range limited to humans because human fecal contamination represents the greatest hazard to humans, yet is a relatively easy nonpoint source to remedy. Watersheds with human fecal contamination could be given first priority for cleanup. A fecal indicator bacterium with a host range limited to humans and a few other warm-blooded animal species would also simplify microbial source tracking because only a few animal species would be required for any host origin database. The literature suggests that the fecal indicator bacterium Enterococcus faecalis has a limited host range. On this basis, we selected this bacterium for study. Of 583 fecal streptococcal isolates obtained on Enterococcosel agar from Canada goose, cattle, deer, dog, human, chicken, and swine, 392 were considered presumptive enterococci and were subsequently speciated with the API 20 Strep system. Of these isolates, 22 were Ent. durans (5.6%), 61 were Ent. faecalis (15.6%), 98 were Ent. faecium (25.0%), 86 were Ent. gallinarum (21.9%), and 125 were unidentified (31.9%). The host range of the Ent. faecalis isolates was limited to dogs, humans, and chickens. Media were developed to isolate and identify Ent. faecalis quickly from fecal samples and this scheme eliminated Ent. faecalis isolates from dogs. When the remaining Ent. faecalis isolates were ribotyped, it was possible to differentiate clearly among the isolates from human and chicken. It may be that combining the potentially limited host range of Ent. faecalis with ribotyping is useful for prioritizing watersheds with fecal contamination.
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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 | 0.000 | 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 it