Ractopamine and Other Growth-Promoting Compounds in Beef Cattle Operations: Fate and Transport in Feedlot Pens and Adjacent Environments
Bibliographic record
Abstract
Abstract The current study represents a comprehensive investigation of the occurrence and fates of trenbolone acetate (TBA) and metabolites 17α-trenbolone (17α-TBOH), 17β-TBOH, and trendione (TBO); melengesterol acetate (MGA); and the less commonly studied β-andrenergic agonist ractopamine (RAC) in two 8 month cattle feeding trials and simulated rainfall runoff experiments. Cattle were administered TBA, MGA, or RAC, and their residues were measured in fresh feces, pen floor material, and simulated rainfall runoff from pen floor surfaces and manure-amended pasture. Concentrations of RAC ranged from 3600 ng g–1, dry weight (dw), in pen floor to 58 000 ng g–1 in fresh feces and were, on average, observed at 3–4 orders of magnitude greater than those of TBA and MGA. RAC persisted in pen floors (manure t1/2 = 18–49 days), and contamination of adjacent sites was observed, likely via transport of windblown particulates. Concentrations in runoff water from pen floors extrapolated to larger-scale commercial feedlots revealed that a single rainfall event could result in mobilization of gram quantities of RAC. This is the first report of RAC occurrence and fate in cattle feedlot environments, and will help understand the risks posed by this chemical and inform appropriate manure-management practices.
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 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 | 0.000 | 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) | 0.001 | 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".