Genotyping of Canadian field strains of infectious bursal disease virus
Bibliographic record
Abstract
For this retrospective study, infectious bursal disease virus (IBDV) was detected in 134 bursal samples that originated from flocks with conditions such as airsacculitis, tracheitis, pneumonia, septicaemia, inclusion body hepatitis, coccidiosis, and/or a history of production problems without overt clinical symptoms. Samples were from seven Canadian provinces: Ontario, Quebec, Manitoba, British Columbia, Nova Scotia, Alberta, and Newfoundland and Labrador. Viral RNA was identified in bursae with moderate to severe and acute to chronic bursal damage. The ages of the flocks from which samples were collected ranged from 3 to 63 days. Following reverse transcriptase-polymerase chain reaction the nucleotide sequence of the VP2 hypervariable region was determined and compared with sequences available in GenBank. The most common Canadian IBDV field strains were North-American variant viruses. Forty-four viruses were highly related (97.5% to 100.0%) to the US IBDV strain NC171. Moreover, 16 field viruses whose VP2 sequences were 99.2% to 100% identical to the South African 05SA8 IBDV strain appeared closely related to the NC171 group. Delaware E-related field viruses, 98.3% to 100.0% identical to the prototype virus, were identified in 33 samples. Thirty-four Canadian IBDVs showed the highest identity, 94.2% to 98.3%, to US IBDV strain 586. Five samples contained vaccine-related viruses, while two field strains showed the best match to Del A (United States) and IBDV strains SP_04_02 (Spain). Very virulent IBDVs were not detected in Canada.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".