Degradation of antimicrobial resistance genes within stockpiled beef cattle feedlot manure
Bibliographic record
Abstract
Degradation of antimicrobial resistance genes (ARG) in manure from beef cattle administered (kg−1 feed) 44 mg of chlortetracycline (CTC), 44 mg of chlortetracycline plus sulfamethazine (CTCSMZ), 11 mg of tylosin (TYL), or no antimicrobials (Control) was examined. Manure was stockpiled and quantitative PCR (qPCR) was used to assess tetracycline [tet(C), (L), (M), (W)], erythromycin [erm(A), (B), (F), (X)], and sulfamethazine [sul(1), (2)] ARG and 16S rDNA. After 102 d, copies of all ARG decreased by 0.3 to 1.5 log10 copies (g dry matter)−1. Temperature in the interior of piles averaged ≥ 55 °C for 10 d, except for CTCSMZ, but did not reach 55 °C at pile exteriors. Compared to Control, CTCSMZ increased (P < 0.05) tet(C), tet(M), tet(W), sul(1), and sul(2) in stockpiled manure. Copies of 16S rDNA remained higher (P < 0.05) in CTCSMZ than Control for the first 26 d. Levels of most ARG did not differ between the interior and exterior of stockpiles. Our results suggest that stockpiled manure would still introduce ARG to land upon manure application, but at levels lower than if manure was applied fresh.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".