Identifying management and disease priorities of Canadian dairy industry stakeholders
Bibliographic record
Abstract
The objective of this study was to identify the key management and disease issues affecting the Canadian dairy industry. An online questionnaire (FluidSurveys, http://fluidsurveys.com/) was conducted between March 1 and May 31, 2014. A total of 1,025 responses were received from across Canada of which 68% (n=698) of respondents were dairy producers, and the remaining respondents represented veterinarians, university researchers, government personnel, and other allied industries. Participants were asked to identify their top 3 management and disease priorities from 2 lists offered. Topics were subsequently ranked from highest to lowest using 3 different ranking methods based on points: 5-3-1 (5 points for first priority, 3 for second, and 1 for first), 3-2-1, and 1-1-1 (equal ranking). The 5-3-1 point system was selected because it minimized the number of duplicate point scores. Stakeholder groups showed general agreement with the top management issue identified as animal welfare and the number one health concern as lameness. Other areas identified as priorities were reproductive health, antibiotic use, bovine viral diarrhea, and Staphylococcus aureus mastitis with these rankings influenced by region, herd size, and stakeholder group. This is the first national comprehensive assessment of priorities undertaken in the Canadian dairy industry and will assist researchers, policymakers, program developers, and funding agencies make future decisions based on direct industry feedback.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".