Dissipation kinetics and mobility of chlortetracycline, tylosin, and monensin in an agricultural soil in Northumberland County, Ontario, Canada
Bibliographic record
Abstract
A robust high-throughput method was refined to extract three growth-promoting antibiotics, tylosin (TYL), chlortetracycline (CTC), and monensin (MON), from soil. Analysis was performed by electrospray liquid chromatography tandem mass spectrometry. Soil dissipation rate studies were performed in a farm field soil for antibiotics applied with and without manure. Tylosin, CTC, and MON followed first-order dissipation kinetics with half-lives of 4.5, 24, and 3.3 d, respectively, with the addition of manure and 6.1, 21, and 3.8 d, respectively, without manure. Manure application significantly increased TYL dissipation rate, perhaps because of the introduced microbial flora, but had no significant effect on CTC or MON. Monensin dissipation half-life was found to be much shorter in the field study than in a controlled laboratory study, perhaps because of differences in microbial communities. The antimicrobials were not highly mobile. Chlortetracycline was the only antibiotic detected at 25 to 35 cm depth and only up to 2% of the initial concentration in a sandy loam soil. These antibiotics are therefore expected to degrade primarily in agricultural soils before moving to greater depths or to groundwater in significant concentrations in most agricultural systems.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".