Managing Lead Exposure and Toxicity in Cow–Calf Herds to Minimize the Potential for Food Residues
Bibliographic record
Abstract
Lead poisoning is commonly diagnosed in cattle. In this study, 3 groups of cattle from different herds accidentally exposed to discarded lead batteries on pasture were intensively studied to determine the extent and severity of exposure. The losses from acute death due to lead toxicity were substantial in all the 3 study groups at 12%, 17%, and 4%. Blood samples were taken from all cattle around the time of the first diagnosis and then later in 2 of the 3 herds to monitor the change in lead concentrations over time. Asymptomatic lead toxicosis was observed in these herds. In these 3 groups, between 4% and 12% of asymptomatic cattle had blood lead concentrations consistent with acute lead poisoning (> 0.35 ppm), and between 7% and 40% of these asymptomatic animals were in the high-normal range (0.1-0.35 ppm). Because of the consistently high number of asymptomatic cattle with elevated lead levels, all cattle potentially exposed to a lead source should be tested before sale or slaughter to minimize the entry of lead into the food chain. The blood lead concentrations, which were monitored for months after the initial diagnosis, decreased slowly after the cattle were removed from the lead source. The prolonged retention of lead may be due to continued release and absorption of lead from metal particles in the reticulum or rumen. The mean reduction in the lead level was 0.046 ppm (95% CI, 0.017-0.075 ppm) every 30 days for these 2 herds. Using a single-component exponential model, the half-life of lead in the animals retested from Herds 1 and 2 was highly variable. The median half-life was 63 days (interquartile range, 34-107 days). One out of 8 pregnant heifers with high blood levels had a stillborn calf. There were no abortions or calf mortalities in this group. Blood samples were'collected from the calves around the time of birth. The concentrations of lead in the blood of the calves exposed in utero were low (0.010-0.095 ppm).
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".