DETECTION OF SUBCLINICAL MASTITIS IN A DAIRY FARM IN BENI-SUEF CITY, EGYPT
Bibliographic record
Abstract
A total of 116 quarter milk samples were collected aseptically from apparently healthy udders of 29 cows in a dairy farm in Beni-Suef city, Egypt; for detection of subclinical mastitis using California mastitis test (CMT), somatic cell count (SCC), chemical and microbiological examination. Thirteen cows (44.83%) were subclinically mastitic with 27 mastitic quarters (23.28%).The scores of CMT showed 11 quarters (40.74%) as +1 and 16 quarters (59.26%) as +2. The SCC of fore left (FL) quarter milk samples was 4.3×105±1.2×105, while of fore right (FR) quarter milk samples was 3.8×105 ±1.1×105, but for SCC of hind left (HL) quarter milk samples was 2.4×105±9.5×104 and SCC of hind right (HR) quarter milk samples was 2.2×105±7.9×104. The isolated micro-organisms from the examined milk samples were Staphylococcus aureus, Coagulase negative Staphylococci (CNS), Streptococcus spp , E.coli and Aspergillus fumigatus. The present study assured that the indirect tests of subclinical mastitis are more suitable for selecting cows with intramammary infections for subsequent bacteriological sampling.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".