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Record W3009795769 · doi:10.3138/jammi.2019-0015

Emergence of a clone of invasive <i>fucK</i>-negative serotype e <i>Haemophilus influenzae</i> in British Columbia

2020· article· en· W3009795769 on OpenAlexaffvenueabout
Kathleen Whyte, Linda Hoang, Inna Sekirov, Michelle Shuel, William Hoang, Raymond S. W. Tsang

Bibliographic record

VenueJournal of the Association of Medical Microbiology and Infectious Disease Canada · 2020
Typearticle
Languageen
FieldImmunology and Microbiology
TopicBacterial Infections and Vaccines
Canadian institutionsBC Mental Health & Substance Use ServicesPublic Health Agency of Canada
Fundersnot available
KeywordsHaemophilus influenzaeSerotypeMicrobiologyPulsed-field gel electrophoresisOperonBiologyVirologyGenotypeGeneticsGeneEscherichia coliAntibiotics

Abstract

fetched live from OpenAlex

Background: disease, with most infections now caused by non-typeable (non-encapsulated) and non-Hib encapsulated strains. Methods: (Hie) from British Columbia that were determined to have complete deletion of their fucose operon genes. These nine isolates were recovered from blood cultures of three female and six male patients during 2011-2018, with eight recovered in the past 4 years. Results: All nine isolates were biotype IV, with eight showing identical pulsed field gel electrophoresis (PFGE) profiles, whereas the ninth showed 95% similarity. PFGE analysis also showed these fucose operon-negative Hie to be most (94%) similar to the multi-locus sequence type (ST)-18, the most common ST among Hie in British Columbia. These nine fucose operon-negative Hie represented 27.3% of the 33 invasive Hie isolated in British Columbia from 2010 to 2018. Conclusion: Deletion of the fucose operon did not appear to impact the transmission ability of these strains or their ability to cause invasive disease.

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 score0.177
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 studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.204
Teacher spread0.198 · 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

Citations1
Published2020
Admission routes3
Has abstractyes

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Same venueJournal of the Association of Medical Microbiology and Infectious Disease CanadaSame topicBacterial Infections and VaccinesFrench-language works237,207