Evaluation of measurements of the conductivity of quarter milk samples for the early diagnosis of mastitis
Bibliographic record
Abstract
Measurements of the conductivity of quarter milk samples were made in 31 cows in a 70-cow herd in southeast England, for a period of 15 weeks. Over this period, 42 per cent of cow-weeks and 20 per cent of quarter-weeks had an increase in quarter milk conductivity of 10 per cent of more compared with the mean conductivity of the previous 14 milkings. Fourteen per cent of quarter-weeks had an increase in conductivity of 15 per cent or more. The geometric mean somatic cell count (cell count) was higher in quarter-weeks with a 10 per cent or greater increase in conductivity than in quarter-weeks with a conductivity change of less than 10 per cent. At a conductivity threshold of 10 or 15 per cent and a cell count threshold of 200,000 or 400,000 cells/ml the specificity of this system was estimated to be 85 to 92 per cent, the sensitivity 40 to 54 per cent, the negative predictive value 87 to 93 per cent and the positive predictive value 33 to 55 per cent. The positive predictive value of the individual quarter milk conductivity was insufficiently accurate to be used as the sole criterion for the selection of quarters for early antibiotic treatment.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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 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".