BULK TANK SOMATIC CELL COUNT IN MILK SAMPLES FROM STATE OF PARANÁ
Bibliographic record
Abstract
This research studied somatic cell count in bulk tank milk samples (BTSCC) from the state of Paraná, Brazil, at the Milk Quality Laboratory of the Dairy Herd Analysis Service of the Holstein Association of Paraná, the result of technical and scientific cooperation between UFPR and McGill University of Canada. A total of 1,950,034 bulk tank milk samples from ten regions of the state of Paraná were analyzed between January 2005 and April 2012 and were studied using PROC GLM (SAS, version 9.3). Fixed effects were the month and year of analysis, region and age of the sample. Means and standard deviations of BTSCC were 553,519 ± 545,532 cells/ml, respectively. All fixed effects were statistically significant (P<0.01). Highest values for BTSCC are observed in the month of February (554,000 cells/ml ± 1.45) and lowest values in September (450,000 cells/ml ± 1.47). Similarly, the highest values were found in the year 2010 (567,000 cells/ml ± 1.16), the lowest BTSCC was found in 2012 (444,000 cells/ml ± 1.57). The region effect was also significant with the highest values found in the South Center/ Guarapuava (668,000 cells/ml ± 0.87) and the lowest in the Southwest/ Francisco Beltrão (359,000 cells/ml ± 2.00). Both variables showed a reduction of their values with increasing age of the sample, from 518,000 ± 1.08 to 472,000 cells/ml ± 2.14 between the first and the seventh day, for the BTSCC. Coefficient of variation for BTSCC was 96.10%. The R² was 0.39 for BTSCC.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".