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Record W2899548782 · doi:10.1139/cjm-2018-0376

Identification of <i>Borrelia bissettii</i> in <i>Ixodes scapularis</i> ticks from New Brunswick, Canada

2018· article· en· W2899548782 on OpenAlexaffvenueabout
Julie Lewis, Vett K. Lloyd

Bibliographic record

VenueCanadian Journal of Microbiology · 2018
Typearticle
Languageen
FieldImmunology and Microbiology
TopicVector-borne infectious diseases
Canadian institutionsMount Allison University
Fundersnot available
KeywordsIxodes scapularisBorrelia burgdorferiLyme diseaseBorreliaBiologyIxodesTickTick-borne diseaseVirologyMicrobiologyIxodidaeImmunologyAntibody

Abstract

fetched live from OpenAlex

Lyme disease is a tick-borne disease that is emerging in Canada. The disease is caused by spirochetes of the Lyme borreliosis group, which is expanding as new species are discovered. In Canada, Lyme disease risk has so far been assessed primarily by detection of Borrelia burgdorferi sensu stricto. Of Ixodes scapularis ticks collected between 2014 and 2016 in New Brunswick, Canada, 7 were shown to be infected with Borrelia bissettii by nested PCR and sequencing of 5 B. bissettii genes. Since different Borrelia species are associated with different clinical manifestations and are not detected with the same diagnostic tests, the identification of a previously undocumented or underreported pathogenic Borrelia species has important implications for public and veterinary medicine.

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 score0.042
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.006
GPT teacher head0.202
Teacher spread0.196 · 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
Published2018
Admission routes3
Has abstractyes

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