A survey of recommended practices made by veterinary practitioners to cow-calf operations in the United States and Canada
Bibliographic record
Abstract
Practicing veterinarians (n = 148) who service commercial beef cow-calf herds responded to a survey describing general recommendations made to their clients in terms of vaccine protocol, health, and production practices. Responding veterinarians represented 35 states in the United States and 3 provinces in Canada. More than 50% of responding veterinarians devote over 50% of their practice to service commercial cow-calf producers. The largest group (33%) of veterinarians have been in practice for over 30 yr. Thirty-nine percent of responding veterinarians serviced more than 10,000 cows. Genetic advice is provided by 54% of practicing veterinarians. When vaccinating at branding, the most common recommended vaccines are clostridial (96%), infectious bovine rhinotracheitis (IBR; 94%), bovine respiratory syncytial virus (BRSV; 91%), parainfluenza-3 (PI-3; 90%), and bovine viral diarrhea (BVD) Types 1 and 2 (78 and 77%, respectively). When vaccinating before weaning, the most common recommended vaccines are IBR (99%), BRSV (98%), BVD Types 1 and 2 (96%), PI-3 (93%), clostridial (77%), and Mannheimia haemolytica (77%). When vaccinating after weaning, the most common recommended vaccines are BVD Type 2 (97%), IBR (97%), BVD Type 1 (96%), BRSV (96%), and PI-3 (91%). Over 60% of responding veterinarians recommended that the last preventative vaccine should be administered to cattle 7 to 21 d before shipping. The largest number of respondents (38%) recommended that the earliest age their clients should wean their calves is 90 to 120 d. Castrating bull calves at an age of 0 to 7 d was recommended by 34% of respondents. Calf nutrition is considered as extremely important during a preconditioning program by 82% of responding veterinarians.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".