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Record W1998660777 · doi:10.3201/eid2003.130139

<i>Staphylococcus delphini</i>and Methicillin-Resistant<i>S. pseudintermedius</i>in Horses, Canada

2014· letter· en· W1998660777 on OpenAlexaffabout
Jason W. Stull, Ðurđa Slavić, Joyce D. Rousseau, J. Scott Weese

Bibliographic record

VenueEmerging infectious diseases · 2014
Typeletter
Languageen
FieldMedicine
TopicAntimicrobial Resistance in Staphylococcus
Canadian institutionsUniversity of Guelph
FundersNational Natural Science Foundation of China
KeywordsStaphylococcus pseudintermediusMicrobiologyBiologyBroth microdilutionPulsed-field gel electrophoresisCoagulaseVeterinary medicineMethicillin-resistant Staphylococcus aureusStaphylococcus aureusStaphylococcusAntimicrobialMedicineMinimum inhibitory concentrationGenotypeGeneticsBacteria

Abstract

fetched live from OpenAlex

ecologic interactions between genetically diverse strains (8).In this report, we describe a single case; comparison of disease severity of scrub typhus caused by mixed and single genotype infections should be studied further.Simultaneous infection with multiple antigenic strains of O. tsutsugamushi was detected in an individual mite, Leptotrombidium arenicola (9), a probable vector of scrub typhus.Infection with multiple O. tsutsugamushi strains may be caused by being bitten by multiple mites or by multiple genotypes coexisting within individual mites (7).We ascribed the co-infection to the second cause because the 2 genotypes were simultaneously detected from an eschar sample associated with the bite of 1 mite examined in this study.There may be diverse genotypic co-infection patterns of O. tsutsugamushi.Mechanisms of in-host interactions between genetically diverse strains of O. tsutsugamushi and the initiated host response require the establishment of animal models for further research.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.416
Threshold uncertainty score0.837

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.011
GPT teacher head0.256
Teacher spread0.245 · 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 designCase report
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

Citations21
Published2014
Admission routes2
Has abstractyes

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