An investigation of group and subtype diversity and distribution of porcine rotaviruses in Canadian suckling piglets with diarrhea, 2019-2023
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".