An evaluation of a hand‐held electrical resistance meter for the diagnosis of bovine subclinical mastitis in late lactation under Australian conditions
Bibliographic record
Abstract
OBJECTIVE: To assess the ability of a hand-held device to differentiate between infected and noninfected bovine mammary glands according to the electrical resistance of milk, under Australian conditions. DESIGN: A cross-sectional study. PROCEDURE: Milk samples were collected from 236 quarters of 60 cows selected from a commercial dairy herd with a high prevalence of mastitis. The true infection status of these quarters was determined using bacteriology. Various methods were used in an attempt to relate the electrical resistance of milk from each quarter to the presence or absence of infection in that quarter. RESULTS: Although the electrical resistance of milk from infected quarters was generally lower than that of noninfected quarters, the overlap of readings between the two populations limited the ability of this device to indicate accurately whether a quarter was infected. The use of methods comparing the readings from each of the four quarters of a single cow did not allow the reliable detection of infected cows. CONCLUSION: Although this device may have some practical advantages in comparison with some other methods of diagnosing subclinical mastitis, the predictive value of the method was generally poor.
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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 | 0.004 | 0.009 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".