MétaCan
Menu
Back to cohort
Record W1965701436 · doi:10.1111/vop.12130

Prevalence of methicillin‐resistant <i><scp>S</scp>taphylococcus</i> spp. in the conjunctival sac of healthy dogs

2013· article· en· W1965701436 on OpenAlexaff
Meredith C. Mouney, Jean Stiles, Wendy M. Townsend, Lynn Guptill, J. Scott Weese

Bibliographic record

VenueVeterinary Ophthalmology · 2013
Typearticle
Languageen
FieldMedicine
TopicOcular Infections and Treatments
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsColonizationStaphylococcus pseudintermediusRectumMedicineStaphylococcusVeterinary medicineAnterior naresNoseStaphylococcus aureusMethicillin-resistant Staphylococcus aureusInternal medicineBiologySurgeryMicrobiologyBacteria

Abstract

fetched live from OpenAlex

OBJECTIVES: To determine the prevalence of selected coagulase-positive methicillin-resistant Staphylococcus aureus (MRS) in the conjunctival sac in a group of healthy dogs and to compare the prevalence of ocular MRS colonization with colonization of typically assessed body sites including the nasal cavity and rectum. ANIMALS STUDIED: 123 healthy dogs were used in the prevalence study: 40 dogs from a shelter and 83 privately owned dogs. PROCEDURES: The sampling procedure included culturing three separate sites per subject in the following order: the lower conjunctival fornices, the nares, and rectum. RESULTS: A low prevalence of 1.6% (2/123) of MRS was detected in healthy dogs. Methicillin-resistant Staphylococcus pseudintermedius was isolated from two dogs, one from a conjunctival swab and the other from a rectal swab. CONCLUSION: The survey data indicate the ocular surface is a potential site of MRS colonization, although the prevalence was low in healthy dogs.

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)0.001
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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.042
GPT teacher head0.321
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

Citations26
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueVeterinary OphthalmologySame topicOcular Infections and TreatmentsFrench-language works237,207