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Isolation of Methicillin-Resistant Staphylococcus aureus from the Environment in a Veterinary Teaching Hospital

2004· article· en· W2023418352 on OpenAlexaffabout
J. Scott Weese, Tara DaCosta, Lea Button, Kathryn Goth, Michael F. Ethier, Kendra Boehnke

Bibliographic record

VenueJournal of Veterinary Internal Medicine · 2004
Typearticle
Languageen
FieldMedicine
TopicAntimicrobial Resistance in Staphylococcus
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsMedicineIsolation (microbiology)Methicillin-resistant Staphylococcus aureusVeterinary medicineStaphylococcus aureusInfection controlTransmission (telecommunications)ContaminationCluster (spacecraft)Staphylococcal infectionsMicrobiologyIntensive care medicineBacteriaBiologyEcology

Abstract

fetched live from OpenAlex

After recognition of a cluster of methicillin-resistant Staphylococcus aureus (MRSA) infection in horses and humans at the Ontario Veterinary College Veterinary Teaching Hospital, environmental contamination with MRSA was evaluated. A total of 260 environmental surfaces were sampled during periods when MRSA-infected horses were hospitalized, and MRSA was isolated from 25/260 sites (9.6%). The most commonly contaminated sites were stalls housing MRSA-positive horses, but other stalls, medical equipment, personal items, and equine restraint devices also were contaminated. The role of the environment in the transmission of MRSA infection to horses or humans is unclear. However, relatively widespread contamination of the hospital environment, as apparently occurs when infected horses are hospitalized, suggests that the environment may be an important source of MRSA infection. This possibility must be taken into consideration when designing infection control and disinfection protocols.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.023
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.028
GPT teacher head0.308
Teacher spread0.280 · 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 source (direct Gemma or distilled Codex), 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

Citations103
Published2004
Admission routes2
Has abstractyes

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