Bibliographic record
Abstract
【Objective】To study the relationship between subclinical mastitis and nature month,parity,mammary quarter,cow house and lactation month,so as to have a better understanding of the relationship among the environmental factors,subclinical mastitis,physiological state of cows,and to provide a scientific basis for the prevention and treatment.【Method】In this paper,CMT was used to test the subclinical mastitis once a month in a southern cattle farm from November,2008 to April,2009.【Results】The results showed that the positive rate of subclinical mastitis for the second and third lactation was significantly higher than other lactations(P0.01).The new case of the cattle who was in the fifth,the sixth and the ninth lactation month was obviously higher than other cattle(P0.01).And the new case of positive rate in the mammary quarter was higher than that of right quarter.【Conclusion】The incidence of subclinical mastitis increased as the parity and the time of lactation growing.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".