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Record W2755989450 · doi:10.1177/1040638717731491

Multi-locus sequence types of <i>Mycoplasma bovis</i> isolated from Ontario, Canada in the past three decades have a temporal distribution

2017· article· en· W2755989450 on OpenAlexaffabout
Patricia Bell‐Rogers, Lois Parker, Hugh Y. Cai

Bibliographic record

VenueJournal of Veterinary Diagnostic Investigation · 2017
Typearticle
Languageen
FieldImmunology and Microbiology
TopicMicrobial infections and disease research
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsMultilocus sequence typingrpoBHousekeeping geneBiologyGeneticsLocus (genetics)TypingAlleleSequence (biology)GeneGenotype16S ribosomal RNA

Abstract

fetched live from OpenAlex

A total of 217 Mycoplasma bovis isolates cultured from clinical cases in Ontario, Canada, over the past 30 y were selected to be characterized by a multi-locus sequence typing (MLST) method. Eleven housekeeping genes were evaluated for suitability for MLST; 2 loci that had been used in prior MLST schemes, dnaN and metS, along with hsp70 were chosen for further sequence analysis. The remaining loci- adk, efp, gmk, gyrB, polC, rpoB, tpiA, and uvrC genes-were not used because they had little to no sequence variation. The sequence data from the chosen loci ( dnaN, hsp70, metS) generated 28 sequence types (STs), with the 3 loci having 15, 5, and 7 alleles, respectively. These molecular typing results revealed that the STs had a temporal distribution; over the course of 3 decades, some STs disappeared and new STs appeared. Recent isolates had a greater variety of STs, which may indicate that new strains are emerging more rapidly now than in the past.

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 score0.178
Threshold uncertainty score0.357

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
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 head0.050
GPT teacher head0.293
Teacher spread0.243 · 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

Citations7
Published2017
Admission routes2
Has abstractyes

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