Diagnostic accuracy of clinical illness for bovine respiratory disease diagnosis in feedlot beef calves
Bibliographic record
Abstract
Bovine respiratory disease (BRD) diagnosis in feedlots is based on clinical inspection (CI) done once or twice daily by pen-riders or pen-walkers. A diagnosis of BRD is typically established when an animal has visual signs of BRD and a rectal temperature above a threshold (ranging from 103.1 to 104 °F) (39.5 to 40 °C). This diagnostic approach is known to have less than ideal sensitivity (SeCI) and specificity (SpCI). However, accurate estimates of SeCI and SpCI are not available, in part due to the absence of a reference test for antemortem diagnosis of BRO. The objective was to determine the diagnostic accuracy of CI for BRO diagnosis in post-weaned beef calves. The presence of lung lesions at slaughter (LU) was used as an imperfect reference test to determine SeCI and SpCI.
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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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".