Presence of IgG antibodies against reproductive infections in breeding bulls of Magdalena Medio, Colombia
Bibliographic record
Abstract
Background: cattle farming is an important economic activity in several regions of Colombia. However, farmers are unaware of their cattle health status, and particularly of bacterial, parasitic, and viral diseases, which affect reproduction and profitability. Objective: to assess the presence of IgG antibodies against infectious bovine rhinotracheitis (IBR), bovine viral diarrhea (BVD), bovine leukosis, leptospirosis, brucellosis, and Neospora caninum in breeding bulls in the Magdalena Medio of Colombia, according to age, breed, and origin. Methods: a descriptive, cross-sectional study was conducted with 174 male breeding cattle from severalsubspecies. Animals were above 18 months of age and belonged to dual-purpose farms in the Magdalena Medio region. Presence of IgG anti-IBR, BVD, brucellosis, neosporosis, and leukosis antibodies were determinedwith an enzyme-linked immunosorbent assay (ELISA). A sample of 156 males was assessed for leptospirosis using a microscopic agglutination test (MAT) in a dark field. Results: IgG anti-IBR antibodies were found in92.5% of the animals, anti-BVD in 62.6%, anti-Neospora caninum in 79.3%, anti-Brucella abortus in 4.02%, anti-Leptospira pomona in 8.33%, and anti-L. hardjo in 15.38%, with >1:100 titres. Besides, 64.94% prevalence was observed for bovine leukosis. Conclusions: a high prevalence of IgG anti-IBR, IgG anti-BVD, IgG anti-Neospora caninum, IgG anti-leukosis, and IgG anti-lepstospirosis antibodies were observed in Magdalena Medio bulls. With respect to B. abortus, confirmatory and competitive ELISA test should be performed and sanitary standards need to be established. Detection of IgG antibodies among bulls reveals poor sanitary conditions, absent of protective-vaccination antibodies and an urgent need for health control measurements.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".