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Antimicrobial Resistance in <i>Campylobacter</i> spp. Isolated from Ontario Sheep Flocks and Associations between Antimicrobial use and Antimicrobial Resistance

2012· article· en· W1782635973 on OpenAlexafffundabout
Lisa Scott, Paula Menzies, Richard J. Reid‐Smith, B.P. Avery, Scott A. McEwen, Catherine S Moon, Olaf Berke

Bibliographic record

VenueZoonoses and Public Health · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSalmonella and Campylobacter epidemiology
Canadian institutionsPublic Health Agency of CanadaUniversity of Guelph
FundersHealth CanadaCanadian Food Inspection Agency
KeywordsCampylobacterCampylobacter coliNalidixic acidAntimicrobialBiologyCampylobacter jejuniBroth microdilutionTetracyclineMicrobiologyAntibiotic resistanceErythromycinCiprofloxacinVeterinary medicineAntibioticsMedicineBacteriaMinimum inhibitory concentration

Abstract

fetched live from OpenAlex

The objectives of this study were to determine the prevalence of antimicrobial resistance (AMR) in faecal Campylobacter spp. from lambs and adult sheep and associations between antimicrobial use (AMU) and AMR. A total of 275 faecal samples collected during initial and final visits from 51 sheep flocks, including one feedlot, across southern Ontario were tested for the presence of Campylobacter spp. Campylobacter jejuni was detected in 52% (143/275) of the faecal samples, Campylobacter coli in 7% (19/275), Campylobacter lari in 1% (2/275) and 2% (4/275) were non-speciated Campylobacter. Broth microdilution was used to test antimicrobial susceptibility of 162 isolates to nine antimicrobials. Campylobacter jejuni isolates (n = 142) were resistant to tetracycline (39%), ciprofloxacin (4%), nalidixic acid (4%) and telithromycin (1%). C. coli isolates (n = 19) were resistant to tetracycline (74%), and azithromycin, clindamycin, erythromycin, and telithromycin (5%). The C. lari isolate displayed resistance to nalidixic acid. No statistically significant associations were found between AMU and AMR during multivariate modelling in this study.

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.

How this classification was reachedexpand

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)0.001
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 score0.305
Threshold uncertainty score0.924

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.048
GPT teacher head0.252
Teacher spread0.203 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations21
Published2012
Admission routes3
Has abstractyes

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