ENUMERATION AND ANTIBIOTIC RESISTANCE PATTERNS OF FECAL INDICATOR ORGANISMS ISOLATED FROM MIGRATORY CANADA GEESE (BRANTA CANADENSIS)
Bibliographic record
Abstract
Thermotolerant fecal indicator organisms carried by migratory waterfowl may serve as reservoirs of antibiotic resistance. To determine the extent to which such antibiotic resistance markers were present in migratory Canada geese (Branta canadensis) on the Maryland Eastern Shore, we isolated Enterococcus spp. and Escherichia coli from fresh feces and examined the antibiotic resistance profiles of these bacteria. Samples were obtained in October 2002, January 2003, and March 2003. Thermotolerant E. coli counts ranged from 0 to 1.0x10(7) colony forming units (CFU)/0.1g (g-1) wet weight of feces, whereas Enterococcus spp. counts ranged from 1.0x10(2)-1.0x10(7) CFU g-1 wet weight of feces. Primary isolates of each indicator organism were tested against a panel of 10 antibiotics. Greater than 95% of E. coli isolates were resistant to penicillin G, ampicillin, cephalothin, and sulfathiazole; no E. coli were resistant to ciprofloxacin. Enterococcal isolates showed highest resistance to cephalothin, streptomycin, and sulfathiazole; no enterococci were resistant to chloramphenicol. The tetracyclines, streptomycin, and gentamycin provided the greatest discrimination among E. coli isolates; chlortetracycline, cephalothin, and gentamycin resistance patterns provided the greatest discrimination between enterococcal strains. Multiple antibiotic resistance (MAR) profiles were calculated: fall (E. coli=0.499; enterococci=0.234), winter (E. coli=0.487; enterococci=0.389), and spring (E. coli=0.489; enterococci=0.348). E. faecalis and E. faecium, which are recognized human nosocomial pathogens, were cultured from winter (44 and 56%, respectively) and spring (13 and 31%, respectively) fecal samples.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".