Evaluation of the efficacy of intramuscular versus intramammary treatment of subclinical Streptococcus agalactiae mastitis in dairy cows in Colombia
Bibliographic record
Abstract
A randomized controlled trial was performed in 17 Colombian dairy herds to determine the cure risk among cows subclinically infected with Streptococcus agalactiae exposed to 2 antibiotic therapies. Composite milk samples were collected before milking at the onset of the trial (pretreatment) and 2 subsequent times over a period of approximately 63 d. The intramammary application (IMM) of ampicillin-cloxacillin was compared with the intramuscular application (IM) of penethamate hydriodide, and cure risks after an initial and retreatment application were assessed. Cure risk after the initial treatment was higher (82.4%) for the IMM treatment than for IM therapy (65.8%). However, no difference was observed in the cure risk of refractory cases after retreatment (IMM=52.6% vs. IM=51.2%). The cumulative cure risk (both initial and retreatment) was 90.4 and 82.9% for the IMM and IM products, respectively. A 2-level random effects logistic model that controlled for pretreatment cow-level somatic cell count, indicated that IM treatment (odds ratio=0.37) had a lower cure risk than IMM and a tendency for a lower cure risk with increasing baseline somatic cell count. Our findings suggest that both products and administration routes can reduce the prevalence of S. agalactiae in affected herds, but the IMM product had a better efficacy in curing the infection. In addition to the treatment protocol, the cow somatic cell count should be considered when making management decisions for cows infected with S. agalactiae.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".