Persistence of the antimicrobials lincomycin, chlortetracycline, and sulfamethazine in prairie wetlands
Bibliographic record
Abstract
Abstract Antimicrobials used in livestock production can be present in manure via excretion in the feces and/or urine. Application of raw or processed (composted or stockpiled) manure to crop and pasture land as a plant nutrient source can result in antimicrobial transport to surface waters via rainfall or snowmelt runoff. Little is known regarding antimicrobial persistence in aquatic ecosystems. Consequently, dissipation of environmentally relevant concentrations of three veterinary antimicrobials (lincomycin, chlortetracycline, and sulfamethazine) was studied in three wetlands on the Canadian Prairies. Study wetlands were fortified in the fall to simulate antimicrobial transport via rainfall runoff from fall manure applications to the wetland catchments. After fortification, water column concentrations of all three antimicrobials decreased through September and October. Plotting natural logarithm values of antimicrobial concentration against time resulted in linear relationships for all three antimicrobials, indicating that the summation of all dissipation processes for each antimicrobial could be described by first‐order kinetics. The slopes of the three plots were significantly different, indicating that the order of dissipation was lincomycin < sulfamethazine < chlortetracycline. Consequently, the dissipation DT50 (time required for 50% antimicrobial dissipation) values for lincomycin (14.0 d), sulfamethazine (7.0 d), and chlortetracycline (3.3 d) were significantly different. The longer DT50 values of lincomycin and sulfamethazine suggest that environmentally relevant concentrations of these antimicrobials may affect bacterial production in prairie wetlands.
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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 | 0.001 | 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) | 0.000 | 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".