Contamination of hay and haylage with enteric bacteria and selected antibiotic resistance genes following fertilization with dairy manure or biosolids
Bibliographic record
Abstract
The present study evaluated if enteric bacteria or antibiotic resistance genes carried in fecal amendments contaminate the hay at harvest, representing a potential route of exposure to ruminants that consume the hay. In the field experiments, dairy manure was applied to a hay field for three successive growing seasons, and biosolids were applied to a hay field for one growing season. Various enteric bacteria in the amendments were enumerated by viable plate count, and selected gene targets were quantified by qPCR. Key findings include the following: at harvest, hay receiving dairy manure or biosolids did not carry more viable enteric bacteria than hay from unamended control plots. The fermentation of hay did not result in a detectable increase in viable enteric bacteria. The application of dairy manure or biosolids resulted in a few gene targets being more abundant in hay during the first harvest. Fermentation of hay resulted in an increase in the abundance of gene targets, but this occurred with hay from both the amended and control plots. Overall, the application of fecal amendments resulted in an increase in the abundance of some gene targets associated with antibiotic resistance in the first cut hay.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".