Effectiveness of pulsed electromagnetic field therapy (pemft) on bovine mastitis infection based on persistence of bacterial isolates post treatment
Bibliographic record
Abstract
In the US, mastitis infections in dairy cows account for $2-4 billion in financial losses for dairy farms nationwide, and about $200/cow/yr. Early treatment of these cows is crucial for maintaining the income of dairy farmers. The most common bacteria responsible for bovine mastitis include Staphylococcus aureus, Escherichia coli and Streptococcus species. Pulsed electromagnetic field therapy (PEMFT) was used to treat udders of mastitic dairy cattle (15 cows at two dairy farms in Chino and Ontario, CA), and quarter milk (QM) samples were collected to examine the effect of this technique on the fate of infecting pathogens. Samples were taken on day 0, 2, 3, 4, and 5 after PFEMT-treatment to determine the effect of the treatment on reduction of infecting bacteria. Additional QM samples were collected on day 24 and 28 post-PFEMT to verify clinical treatment. Over 380 QM samples were collected. Bacteria were isolated from the milk and morphological and biochemical tests were performed to identify the isolates. Staphylococcus aureus, Streptococcus spp., Bacillus spp. and coliforms were the predominant presumptive species identified. Pathogen-specific PCR protocols were developed to confirm the identity of the bacterial isolates.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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".