Profitability of growth-enhancing technologies in Canadian feeder cattle production
Bibliographic record
Abstract
The Canadian beef industry is experiencing heightened domestic and global demand; however, it is constantly challenged by the extremely narrow profit margins. In an effort to enhance efficiency, the cattle feeding industry has adopted the use of growth-enhancing technologies (GETs), which has resulted in cattle getting to finished weights more quickly. This study focuses on three types of technologies in the feedlot phase of the beef supply chain, including a trenbolone acetate + estradiol (TBA) implant, melengestrol acetate (MGA) feed additive and ractopamine hydrochloride (RAC) feed additive. Previous research has found positive impacts of GETs on animal performance and environmental sustainability; however, economic dimensions have not been as thoroughly explored. Accordingly, this thesis is the first attempt to use recent Canadian feedlot data to determine economic gains from GET adoption by feedlots. The objective of the research conducted for this thesis is to determine the relative profitability of cattle feeding in Canada using GET (conventional) versus non-GET (non-conventional) systems. Supporting objectives are to evaluate and compare measures of animal performance of the treatment groups; and determine the efficiency of conventional and non-conventional systems by estimating the probability distribution of risk. To achieve these objectives, data from a four-year animal trial at the Agriculture and Agri-food Lethbridge Research and Development Center are used, along with supporting price data from CanFax Research Services and Statistics Canada within an enterprise budgeting framework with accompanying risk analysis. Results from the partial enterprise budget indicate that the feeding system which employed TBA has the highest net returns for both heifers and steers; however, results from the risk analysis differ. Using stochastic dominance, feed additives were discovered to be second-degree stochastic dominant for their respective sex class. Further investigation confirms that a production system providing an RAC feed additive to steers is the least likely to generate a negative net return; and likewise for heifers receiving a TBA implant.
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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".