Pilot implementation of a newly developed bovine leukemia virus control program on 11 Alberta dairy farms
Bibliographic record
Abstract
We developed a custom bovine leukemia virus (BLV) control program for the Alberta dairy industry, consisting of a risk assessment and a comprehensive list of best management practices (BMP) aimed at prevention of BLV transmission between cattle. This control program was implemented on 11 farms for approximately 1 yr. Blood samples were collected from all cattle ≥12 mo old, and serum was tested with a commercial ELISA. Risk assessments were performed on each farm, risk-connected on-farm management was identified, and management changes expected to prevent transmission of BLV between cattle were suggested by the first author and agreed upon with each farmer. Throughout the following year, all participating farmers were visited multiple times to identify and overcome barriers to implementation and to monitor progress. After approximately 1 yr of implementing BLV control, all cattle ≥12 mo old on farm with a negative or no previous test result were sampled, and the within-herd prevalence was determined. The median number of cattle on farm that were ≥12 mo was 195 (range 110-524). The initial prevalence averaged 39% (13-66%). On average, 5 BMP (3-7) were suggested to each farmer. On average, 4 BMP (1-7) were implemented. At the second sampling, the average within-herd prevalence of all animals that tested positive (including the previous sampling) was 36% (12-62%). Eight farms reduced their within-herd BLV prevalence, within-herd prevalence stayed constant on 1 farm, and it increased on 1 farm. The remaining farm terminated their participation before the second sampling. The number of seroconversions per farm ranged from 3 to 109, highlighting the success of some producers to minimize new infections. The risk assessment was proven to be a valuable tool to identify flaws in on-farm management, although risk assessment score was unrelated to the within-herd BLV prevalence. Finally, it appeared that implementation of BMP aimed at prevention of BLV transmission between cattle could reduce within-herd BLV prevalence when farmers committed to their implementation.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".