Short communication: The effect of storage conditions and storage duration on milk ELISA results for pregnancy diagnosis
Bibliographic record
Abstract
The objective of this study was to evaluate the effect of storage temperature and time from sample collection to analysis on test classification of a commercially available ELISA for diagnosis of pregnancy using the measurement of pregnancy-associated glycoproteins (PAG) in milk samples from dairy cows. Few studies have evaluated the effects of sample handling on milk PAG results. Using a repeated-measures study design, we evaluated sample storage at 5 temperatures: 37°C, 22°C, 4°C, -20°C, or -80°C. Sample aliquots from 45 cows (20 with a pregnant test result, 10 open, and 15 recheck) were stored for 4, 7, 14, 28, 60, 90, or 365 d. The measured PAG level was influenced by storage duration and condition. Samples stored for 365 d had a slightly increased PAG level, whereas samples stored for all other durations showed a slight decline in PAG level compared with the initial result. The reason for an increase in PAG level following long-term storage is not known. This will not affect dairy producers using the test but may be important in samples stored for research applications. The changes in PAG level were small and within the expected variation for this test. Fewer than 6% of samples changed in classification and, as expected, they were samples near the test interpretation cut-points.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".