Bibliographic record
Abstract
North American dairy herds are commonly infected with bovine leukemia virus (BLV), with production-limiting effects, reduced animal welfare and consumer concerns. The overall goal of this thesis was the development of an adaptable on-farm BLV control program. To summarize important background knowledge and understand all aspects of BLV control, I performed the following: 1) Available literature concerning BLV transmission and control was reviewed and summarized. 2) Five commercially available ELISA were evaluated and compared, using 160 serum samples from Alberta cattle. 3) Economic impacts of BLV and its control were evaluated by creating an economic model of an average Alberta dairy farm. 4) Motivators and barriers for Alberta dairy farmers to change behavior on farm and implement BLV control measures were investigated by analyzing conversations with farmers as well as veterinarians. 5) In those conversations, dairy farmers’ and veterinarians’ opinions toward various BLV control measures were sought to adjust the BLV control program. 6) Based on findings, a risk assessment tool was designed to identify and weigh on-farm behavior that could cause transmission of BLV between animals. When this risk assessment tool was used on 11 Alberta dairy farms, its results, in combination with serum test results, led to the recommendation of tailored best-management practices aimed at preventing BLV transmission between animals. Implementation, within-herd prevalence, and seroconversions were measured. 7) Finally, all findings were summarized and discussed. In conclusion, recommendations for BLV control have not changed over a long interval, as general principles remain relevant. Additionally, identification of BLV-infected animals is easy and reliable. Although BLV control relies on financial investments, it has an overall economic net benefit. Motivating farmers to implement BLV control is dependent on knowledge and control measures considered feasible by the farmer. Finally, implementation of on-farm BLV control reduced within-herd BLV prevalence for the majority of participating farms.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".