Evaluation of on-farm tools for colostrum quality measurement
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Bibliographic record
Abstract
The objectives of this study were to determine the immunoglobulin G (IgG) content of colostrum on Alberta dairy farms and to determine which on-farm tool, the colostrometer or the Brix refractometer, was more highly correlated with IgG content as determined by radial immunodiffusion (RID). Colostrum samples (n=569) were collected between February and July 2012 from 13 commercial dairy farms in central Alberta, with herds ranging in size from 60 to 300 lactating cows. Immunoglobulin G content was determined directly by RID and indirectly by a colostrometer (specific gravity) and Brix refractometer (total solids). The Spearman correlation was used for the colostrometer and Brix refractometer data. According to RID analysis, 29.1% of the colostrum samples contained <50 mg/mL IgG. Concentrations ranged from 8.3 to 128.6 mg/mL IgG, with a median of 65.1 mg/mL. Third or greater parity cows had higher colostral IgG content (69.5±1.98 mg/mL) than second parity (59.80±2.06 mg/mL) or first parity (62.2±1.73 mg/mL) cows. The colostrometer data were more highly correlated with RID results (r=0.77) than were the Brix refractometer data (r=0.64). Specificity and sensitivity were determined for the colostrometer and Brix refractometer compared with a cut-point of 50 mg/mL IgG as determined by RID. The highest combined value for sensitivity and specificity occurred at 80 mg/mL for the colostrometer (84.1 and 77.0%, respectively) and 23% Brix (65.7 and 82.8%, respectively). This study indicates that although the colostrometer data are better correlated with true IgG values, the user-friendly Brix refractometer is a more specific tool to detect colostrum of adequate quality.
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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 | 0.025 | 0.007 |
| 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 it