Field assessment of horse-associated genetic markers HoF597 and mtCytb for detecting the source of contamination in surface waters
Bibliographic record
Abstract
We investigated the specificity and sensitivity of two horse-associated markers, HoF597 and Horse mtCytb, and 12 mitochondrial and bacterial markers of six animal species (human, cow, pig, bird, dog, chicken) in the faecal samples of 50 individual horses. Both horse markers were detected in 48 (96%) faecal samples. Cross-reactivity with dog (BacCan545) and pig (P23-2) occurred in 88% and 72% of horse faecal samples, respectively. Several other bacterial and mitochondrial markers of non-target hosts were also detected; however, their specificities were >80%. Analyses of samples from surface waters (n = 11) on or adjacent to properties from which horse faecal samples had been collected showed only the presence of HoF597 but not horse mitochondrial marker. Our data suggest that while bacterial and (or) mitochondrial markers of other animal species may be present in horse faeces, dog and pig markers may predominantly be present in horse faecal samples, which points to their nonspecificity as markers for microbial source tracking. Although HoF597 and Horse mtCytb are highly sensitive and specific for the detection of horse faecal pollution, because of their low numbers, mitochondrial (mtDNA) markers may not be robust for screening surface waters.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".