Invited review: Bovine leukemia virus—Transmission, control, and eradication
Bibliographic record
Abstract
Bovine leukemia virus (BLV) infection, endemic in North American dairy herds, has production-limiting effects. A literature review of available papers published since 1995 concerning BLV transmission and its control was conducted. Although confirmed transmission routes were reviewed (blood, natural breeding, in utero, colostrum, and milk), there is still a lack of detailed information on other specific risks for transmission (e.g., contact transmission and hoof-trimming knives). Eradication of BLV has been achieved by combined management, segregation, and culling approaches. In contrast, although sole implementation of best management practices aimed at prevention of BLV transmission has decreased within-herd BLV prevalence, it has not eradicated BLV from a herd. Therefore, control and eradication of BLV by best management practices only should be further investigated. Additionally, the role of proviral load in infected cattle was investigated. Cattle with a high proviral load seem to be more likely to infect others, whereas those with a very low proviral load seem to have low risks of transmitting BLV. Information on proviral load could be taken into account when controlling BLV in high-prevalence herds. In conclusion, there is a need for detailed, large-scale studies investigating roles of specific transmission routes, knowing proviral load of infected individuals.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".