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Record W2536529050 · doi:10.1111/jsap.12586

Comparison of bacterial cultures of the larynx between dogs with laryngeal paralysis and normal dogs

2016· article· en· W2536529050 on OpenAlexaff
Justin B Ganjei, Andreas Langenbach, Gail Watrous, Jennifer L. Hodgson

Bibliographic record

VenueJournal of Small Animal Practice · 2016
Typearticle
Languageen
FieldMedicine
TopicVeterinary Oncology Research
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsLarynxMedicineLaryngeal paralysisParalysisMicrobiological cultureClinical significanceAntimicrobialBacteriaPathologyMicrobiologySurgeryBiology

Abstract

fetched live from OpenAlex

OBJECTIVE: To document the most common types of bacteria isolated from the canine larynx and to compare isolates, degree of growth and susceptibility patterns between dogs with laryngeal paralysis and dogs with normal laryngeal function. METHODS: Laryngeal swabs were collected from each patient and submitted for bacterial culture and susceptibility testing. Dogs with laryngeal paralysis (n=23) underwent a unilateral arytenoid lateralisation and control dogs (n=24) underwent an elective orthopaedic procedure. Results of the cultures were compared between groups. RESULTS: Bacterial organisms isolated from the larynx were similar to those normally found in the oropharynx, trachea and lungs. The most common bacteria isolated from the larynges of all dogs were Escherichia coli, Klebsiella species and Pasteurella species. Pure colonies were more commonly seen in dogs with laryngeal paralysis while mixed colonies were more commonly seen in control dogs. Antimicrobial resistance was similar between study and control dogs. CLINICAL SIGNIFICANCE: The laryngeal flora appears to contain bacteria that are commonly isolated from the oropharynx, trachea and lungs. Differences in antimicrobial susceptibility were not identified between study and control 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 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 score0.269
Threshold uncertainty score0.249

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 communication0.0000.001
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 head0.067
GPT teacher head0.395
Teacher spread0.327 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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