Efficacy of Two Hydrogen Peroxide Teat Disinfectants Against Staphylococcus aureus and Streptococcus agalactiae
Bibliographic record
Abstract
An experimental teat dip containing 0.5% hydrogen peroxide as the active ingredient was compared with a teat disinfectant also containing 0.5% hydrogen peroxide that is commercially available throughout North America. The study was conducted under conditions of experimental challenge with a positive control following the guidelines recommended by the National Mastitis Council. The efficacy of the test product and the positive control product were compared in 45 cows, with 89 total teats receiving each product after milking during a 10-wk study period. There was no significant difference between the experimental hydrogen peroxide product and the positive control in new intramammary infections caused by Staphylococcus aureus (27.0 and 18.0% in the treatment groups, respectively). Additionally, there was no significant difference between the experimental product (6.7%) and the positive control groups (4.5%) in new intramammary infections caused by Streptococcus agalactiae. Traditional analysis of teat skin condition changes supported improved teat skin condition with the test disinfectant. After accounting for the correlation of teats within cow, significant differences were also observed between the treatment groups for teat skin condition. The experimental hydrogen peroxide-based teat disinfectant provided efficacy similar to that of the positive control teat disinfectant, with significant improvement in teat skin condition and no adverse effects on teat end condition.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".