An Investigation of the Classification, Seasonality, and Genotype Diversity of Rotavirus in Swine Populations in Canada
Bibliographic record
Abstract
Rotavirus is an important cause of acute gastroenteritis affecting swine globally and this thesis examined important characteristics of rotavirus in swine populations in Canada to enhance current disease control practices. A classification tool was developed using machine learning alongside alignment-based methodology for dual classification of group A rotavirus genotypes and demonstrated strong performance. Seasonality of group A, B, and C rotaviruses was explored through descriptive analysis, time-series decomposition, and statistical analysis of surveillance data obtained from a diagnostic laboratory and was identified to not be present in Canada between 2016-2020. Genotype diversity of group A, B and C rotaviruses was investigated between 2011-2021 and no major shifts in the patterns of circulating genotypes were identified in group A and B rotaviruses, although proportion of laboratory positivity for genotype G6 of group C rotaviruses showed an increasing trend when evaluated descriptively on an annual basis.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 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".