Effectiveness of sorting calves with high risk of developing bovine respiratory disease on the basis of serum haptoglobin concentration at the time of arrival at a feedlot
Bibliographic record
Abstract
OBJECTIVE: To evaluate serum haptoglobin concentration at feedlot arrival and subsequent performance and morbidity and mortality rates of calves that developed bovine respiratory disease. ANIMALS: 360 heifer calves and 416 steer and bull calves. PROCEDURES: Serum samples were obtained from cattle at the time of arrival to a feedlot (day -1) and analyzed for haptoglobin concentration. In experiment 1, calves were classified into groups with a low (< 1.0 μg/mL), medium (1.0 to 3.0 μg/mL), or high (> 3.0 μg/mL) serum haptoglobin concentration and allotted into pens on the basis of group. In experiment 2, calves were classified as having or not having detectable serum haptoglobin concentrations. RESULTS: In experiment 1, average daily gain from days 1 to 7 decreased as haptoglobin concentration increased. Dry-matter intake (DMI) from days 1 to 21 decreased with increasing haptoglobin concentration, and DMI typically decreased from days 1 to 63. Total bovine respiratory disease morbidity rate typically increased with increasing haptoglobin concentration. At harvest, no differences in carcass characteristics were observed on the basis of haptoglobin concentration. In experiment 2, cattle with measureable serum haptoglobin concentrations at arrival weighed less throughout the experiment, gained less from days 1 to 7, and had lower DMI from days 1 to 42. Overall morbidity rate was not different between groups, but cattle with detectable serum haptoglobin concentrations had higher odds of being treated 3 times. CONCLUSIONS AND CLINICAL RELEVANCE: Serum haptoglobin concentration in cattle at the time of feedlot arrival was not associated with overall performance but may have limited merit for making decisions regarding targeted prophylactic treatment.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".