Bibliographic record
Abstract
Avian bornaviruses (ABV), identified in 2008, infect captive parrots and macaws worldwide. The natural reservoirs of these viruses are unknown. Reverse transcription-PCR (RT-PCR) was used to screen oropha-ryngeal/cloacal swab and brain samples from wild Canada geese (Branta canadensis) for ABV. Approximately 2.9 % of swab samples were positive for bornavirus sequences. Fifty-two percent of brain samples from 2 urban flocks also tested positive, and brain isolates were cultured in duck embryo fibroblasts. Phylogenetic analyses placed goose isolates in an independent cluster, and more notably, important regulatory sequences present in Borna disease virus but lacking in psittacine ABVs were present in goose isolates. Borna disease virus (BDV) is a nonsegmented negative-strand RNA virus (order Mononegavirales, genus Bornaviridae) best known for causing neurologic disease in horses in central Europe, where the virus is likely transmitted via shrew urine (9, 15). While BDV is considered an infectious agent of mammals, there have been reports of BDV-associated infections in birds. Malkinson and colleagues identified BDV as the cause of a neurologic disease in captive ostriches (12), and Berg et al.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.595 | 0.373 |
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".