MétaCan
Menu
Back to cohort
Record W2030792975 · doi:10.1089/fpd.2009.0400

Antimicrobial Drug Use and Antimicrobial Resistance in Enteric Bacteria Among Cattle from Alberta Feedlots

2009· article· en· W2030792975 on OpenAlex
Sangeeta Rao, Joyce Van Donkersgoed, Valerie Bohaychuk, Thomas E. Besser, Xinming Song, Bruce A. Wagner, Dale D. Hancock, David G. Renter, David A. Dargatz, Paul S. Morley

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueFoodborne Pathogens and Disease · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSalmonella and Campylobacter epidemiology
Canadian institutionsAgriculture Food and Rural Development
Fundersnot available
KeywordsNalidixic acidCampylobacterAntibiotic resistanceSalmonellaTetracyclineCiprofloxacinAntimicrobialStreptomycinFecesBiologyVeterinary medicineDrug resistanceMicrobiologyFeedlotCampylobacter jejuniAntibioticsMedicineBacteriaAnimal science

Abstract

fetched live from OpenAlex

The purpose of this study was to determine whether antimicrobial resistance (AMR) in foodborne pathogens (Escherichia coli O157, Salmonella, and Campylobacter) and non-type-specific E. coli obtained from fecal samples of feedlot cattle was associated with antimicrobial drug (AMD) use. A secondary objective was to determine if AMR in non-type-specific E. coli could be used as a predictor of AMR in foodborne pathogens. Fecal samples were collected from pen floors in 21 Alberta feedlots during March through December 2004, and resistance prevalence was estimated by season (Spring, Fall) and cattle type (fewest days-on-feed and closest to slaughter). AMD exposures were obtained by calculating therapeutic animal daily doses for each drug before sampling from feedlot records. Generalized linear mixed models were used to investigate the relationship between each AMR and AMD use. Non-type-specific E. coli was commonly recovered from fecal samples (88.62%), and the highest prevalence of resistance was found toward tetracycline (53%), streptomycin (28%), and sulfadiazine (48%). Campylobacter jejuni was recovered from 55.3% of the fecal samples, and resistance was generally less for the drugs that were evaluated (doxycycline 38.1%, ciprofloxacin 2.6%, nalidixic acid 1.64%, erythromycin 1.2%). E. coli O157 and Salmonella were recovered much less frequently (7% and 1% prevalence, respectively). The prevalence of recovery for the bacteria studied varied between seasons and cattle types, as did patterns of AMR. Among non-type-specific E. coli, resistance to tetracycline, streptomycin, and sulfadiazine was found to be positively associated with in-feed exposure as well as injectable tetracycline, but these differences were relatively small and of questionable practical relevance. Among C. jejuni isolates, cattle type was significantly associated with doxycycline resistance. Results suggested that resistance in non-type-specific E. coli to chloramphenicol, trimethoprim/sulfamethoxazole, and tetracycline might be used as predictors of resistance to these drugs in E. coli O157 recovered from the same fecal samples.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.262
Threshold uncertainty score0.466

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.203
Teacher spread0.189 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it