Detection of polyoma and corona viruses in bats of Canada
Bibliographic record
Abstract
Several instances of emerging diseases in humans appear to be caused by the spillover of viruses endemic to bats, either directly or through other animal intermediaries. The objective of this study was to detect, identify and characterize viruses in bats in the province of Manitoba and other regions of Canada. Bats were sampled from three sources: live-trapped Myotis lucifugus from Manitoba, rabies-negative Eptesicus fuscus, M. lucifugus, M. yumanensis, M. septentrionalis, M. californicus, M. evotis, Lasionycteris (L.) noctivagans and Lasiurus (Las.) cinereus, provided by the Centre of Expertise for Rabies of the Canadian Food Inspection Agency (CFIA), and L. noctivagans, Las. cinereus and Las. borealis collected from a wind farm in Manitoba. We attempted to isolate viruses from fresh tissue samples taken from trapped bats in cultured cells of bat, primate, rodent, porcine, ovine and avian origin. We also screened bat tissues by PCR using primers designed to amplify nucleic acids from members of certain families of viruses. We detected RNA of a group 1 coronavirus from M. lucifugus (3 of 31 animals) and DNA from an as-yet undescribed polyomavirus from female M. lucifugus (4 of 31 animals) and M. californicus (pooled tissues from two females).
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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".