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Record W2036487046 · doi:10.4102/jsava.v82i2.38

In vitro antimicrobial susceptibility of Staphylococcus aureus strains from dairy herds in KwaZulu-Natal

2011· article· en· W2036487046 on OpenAlexaff
Tracy Schmidt

Bibliographic record

VenueJournal of the South African Veterinary Association · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMilk Quality and Mastitis in Dairy Cows
Canadian institutionsCascades (Canada)
Fundersnot available
KeywordsMastitisStaphylococcus aureusAntimicrobialPenicillinAmpicillinAntibiotic resistanceTrimethoprimAntibioticsMicrobiologyMedicineVeterinary medicineSulfamethoxazoleBiologyBacteria

Abstract

fetched live from OpenAlex

Staphylococcus aureus is 1 of the most important causes of bovine mastitis and is responsible for significant economic losses to the dairy industry worldwide. One of the principal approaches used in treating intramammary infections is the administration of antimicrobials. Due to the propensity of S. aureus to develop resistance, antimicrobial susceptibility monitoring is necessary to ensure that treatment regimens are effective. As part of this investigation, 90 S. aureus strains isolated from mastitis cases submitted to Allerton Provincial Veterinary Laboratory during 2008 and 2009 were evaluated for their susceptibility to a panel of 10 antimicrobials. Only 8 of the 90 S. aureus isolates tested (8.9%) were found to be susceptible to all of the antimicrobials evaluated. A very high level of resistance to the beta-lactam antibiotics was noted: 47.8% of the isolates were resistant to penicillin and 65.6% were resistant to ampicillin. Minimal resistance to oxacillin, cephalothin and trimethoprim-sulfamethoxazole (1.1%) was found. Seventeen (18.9%) of the isolates tested were found to be resistant to 3 or more antimicrobials. The need for vigilant monitoring of bacterial resistance trends in the dairy industry is warranted as the potential public health implications are significant.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.872
Threshold uncertainty score0.195

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.038
GPT teacher head0.236
Teacher spread0.198 · 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

Citations11
Published2011
Admission routes1
Has abstractyes

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