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Record W2401861246

Antimicrobial susceptibility of Staphylococcus pseudintermedius colonizing healthy dogs in Saskatoon, Canada.

2016· article· en· W2401861246 on OpenAlexaffabout
Roshan Priyantha, M. Casey Gaunt, Joseph E. Rubin

Bibliographic record

VenuePubMed · 2016
Typearticle
Languageen
FieldMedicine
TopicAntimicrobial Resistance in Staphylococcus
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsStaphylococcus pseudintermediusQuinupristinDalfopristinLinezolidClindamycinMicrobiologyMedicineErythromycinAntibiotic resistanceAntimicrobialVancomycinVeterinary medicineStaphylococcusBiologyStaphylococcus aureusAntibioticsBacteria
DOInot available

Abstract

fetched live from OpenAlex

This study reports antimicrobial susceptibility of Staphylococcus pseudintermedius carried by healthy dogs in Saskatoon, and describes changes in antimicrobial resistance since a 2008 study. One hundred healthy dogs presenting to the wellness service at the Western College of Veterinary Medicine were screened for S. pseudintermedius by culturing rectal and pharyngeal swabs. Staphylococcus pseudintermedius was identified biochemically and antimicrobial minimum inhibitory concentrations were determined by broth microdilution. Methicillin resistance was confirmed by polymerase chain reaction (PCR) and sequencing of the mecA gene. Of 221 S. pseudintermedius isolates from 78 dogs, 7 were methicillin resistant. No resistance to the fluoroquinolones, nitrofurantoin, tigecycline, vancomycin, quinupristin-dalfopristin, linezolid, or daptomycin was identified. Of the 78 positive dogs, isolates resistant to penicillin were found in 78%, to ampicillin in 61% and to tetracycline in 26%; resistance to oxacillin, erythromycin, clindamycin, trimethoprim + sulfamethoxazole, chloramphenicol, and gentamicin was found in < 10% of dogs. Compared to the 2008 study, the frequency of resistance to all drugs increased, and the frequency of colonization with pan-susceptible isolates decreased from 46% to 30%.

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)0.001
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 score0.731
Threshold uncertainty score0.920

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.018
GPT teacher head0.243
Teacher spread0.225 · 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

Citations34
Published2016
Admission routes2
Has abstractyes

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