Current feedlot cattle health and well-being program recommendations in the United States and Canada
Bibliographic record
Abstract
Feedlot consulting veterinarians (n=23) in the United States and Canada participated in a beef cattle health and well-being recommendation survey. The objective of the survey was to determine the recommendations of consulting feedlot veterinarians in the United States and Canada for cattle health and well-being, and to compare these recommendations to those made in a survey conducted in 2009. Participants answered 78 questions on feeder cattle husbandry, health, and preventative medicine recommendations. Survey results showed that veterinarians visit feedlots in their practice an average of 1.7 times/month. Feedlot veterinarians train employees on pen riding, processing procedures, necropsy, and many other areas of cattle health and well-being. The majority of veterinarians use Beef Quality Assurance concepts as part of employee training. Veterinarians also give recommendations on routine surgical procedures, such as dehorning and castration, metaphylaxis, feed-grade antibiotics, vaccination programs, and treatment regimens. Morbidity and mortality rates for feedlots consulted were obtained, along with other information about risk factors for morbidity rates. Cattle health risk was considered the most important factor for predicting morbidity in both 2009 and 2014. This survey provides valuable information on the current recommendations of feedlot consulting veterinarians in the United States and Canada, helps track industry changes over time, and offers benchmarking data for the industry.
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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".