Efficacy of a florfenicol-flunixin meglumine combination product versus tulathromycin or ceftiofur crystalline free acid for the treatment of undifferentiated fever in feedlot calves.
Bibliographic record
Abstract
In this field trial, a new combination product containing florfenicol and flunixin meglumine (FLOR-FM) was compared with commercially available products that contained only tulathromycin (TULA) or ceftiofur crystalline free acid (CCFA) for the treatment of undifferentiated fever (UF; rectal temperature >/=105.0 degrees F) in beef calves that received long-acting oxytetracycline at feedlot arrival. The overall mortality rate of the FLOR FM group (2.0%) was significantly (P less than .050) lower than the rates in the TULA and CCFA groups (10.0% and 20.0%, respectively; 50 animals/group), even though the first UF relapse rate of the FLOR FM group was significantly (P less than .050) higher than that of the TULA group. In the FLOR FM group, this resulted in per-animal economic advantages of Can$46.23 (versus TULA) and Can$108.77 (versus CCFA) based on equal costs for initial UF therapy. These results demonstrate that it is more cost-effective to administer FLOR FM than TULA or CCFA for initial UF therapy in feedlot calves at high risk for bovine respiratory disease that receive metaphylactic long-acting oxytetracycline at feedlot arrival.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".