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Record W4403272439 · doi:10.54846/jshap/1400

An investigation of group and subtype diversity and distribution of porcine rotaviruses in Canadian suckling piglets with diarrhea, 2019-2023

2024· article· en· W4403272439 on OpenAlexaboutno aff
Carolina Maciel Malgarin, F. de Grau

Bibliographic record

VenueJournal of Swine Health and Production · 2024
Typearticle
Languageen
FieldMedicine
TopicViral gastroenteritis research and epidemiology
Canadian institutionsnot available
Fundersnot available
KeywordsDiarrheaBiologyVeterinary medicineDistribution (mathematics)VirologyGroup (periodic table)Animal scienceInternal medicineMedicineMathematicsChemistry

Abstract

fetched live from OpenAlex

Objective: To determine the frequency of detection and group diversity of rotavirus (RV) A, B, and C, and G (glycoprotein antigen) serotype (based on viral protein 7 [VP7] gene analysis) infecting suckling piglets with diarrhea in Canadian farms. Materials and methods: Canadian swine veterinarians submitted 1117 enteric samples from suckling piglets between July 2019 and December 2023 to the University of Guelph Animal Health Laboratory for RV group identification and VP7 sequencing for subtyping. Analysis of the VP7 sequence from 837 samples was performed using the Animal Health Sequivity Dashboard (Merck & Co, Inc) and descriptive statistics. Results: Rotavirus A, B, and C were present in 40.7%, 12.5%, and 46.8% of samples, respectively. The most common RV identified was RVC G6, present in 296 samples, followed by RVA G9 in 205 samples. A single RV group was involved in 444 cases (72.3%), while in 170 cases (27.7%), more than one RV group/subtype was detected. Eighteen subtypes were identified by sequencing the VP7 protein (5 RVA, 9 RVB, and 4 RVC). Implications: Rotavirus protection for suckling piglets comes from colostrum and milk. Knowing which RV group is causing diarrhea is important since vaccination does not generate cross-protection among groups. Using molecular diagnostic testing, it is possible to identify the specific group and subtype of RV circulating on the premises and decide the best treatment strategy for the 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 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)0.000
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 score0.046
Threshold uncertainty score0.946

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.029
GPT teacher head0.314
Teacher spread0.285 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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