Evaluation of digital Brix refractometry in assessing maternal colostrum quality and transfer of passive immunity in beef cattle
Bibliographic record
Abstract
Newborn calves depend on passive immunity acquired by the timely ingestion of colostrum containing adequate concentrations of immunoglobulin G (IgG). Failed transfer of passive immunity (FTP) in calves is defined as serum IgG concentrations <10 g/L, measured between 1 and 7 days after birth. It is estimated that up to 27% of beef calves suffer from FTP, which can affect calf health, survival, and growth. In contrast to dairy calves that are typically hand-fed prescribed volumes of colostrum, beef calves ideally suck from their dam and do not need human intervention. This requires the calf to be vigorous, the cow to allow the calf to suckle, and the colostrum to be of sufficient quality and quantity. However, beef producers rarely know the quality or quantity of colostrum available to, or consumed by, the calves in their care. Although measuring the volume of colostrum is not generally feasible for beef producers, there are on-farm tools available to estimate IgG concentration. Optical and digital refractometers are widely used to evaluate colostrum and serum of dairy cattle. However, there is minimal published research evaluating these tools in beef cattle. Objectives of this study were to evaluate the effectiveness of the Brix refractometer for estimating quality of maternal colostrum and levels of passive immunity acquired by commercial beef calves.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".