Animal and farm factors affecting the fatty acid profile and amyloid a concentration of milk on Quebec dairy farms
Bibliographic record
Abstract
Relationships between farm and animal factors and the fatty acid (FA) profile and milk amyloid A (MAA) content of milk were determined in 336 Holstein dairy cows on 24 Quebec farms using multiple regression. Cows with a somatic cell count (SCC) >200 000, and farms feeding palm oil were excluded. Independent factors of the regression models included days in milk (DIM), parity, yield, fat and protein contents of milk, SCC, and the dietary contents of neutral detergent fiber (NDF) and crude fat (CFAT). Nonsignificant variables with P > 0.25 were stepwise removed. Models with high fits were those of total short-chain FA, medium-chain FA, odd- and branched-chain FA (OBCFA), and saturated long-chain FA with R2 of 0.33, 0.36, 0.34, and 0.41, respectively. The fat and protein contents and yield of milk did not affect the milk FA profile. Higher NDF increased the milk fat proportions of short-chain FA and OBCFA and decreased those of monounsaturated (MUFA) and polyunsaturated FA (PUFA). Higher CFAT reduced this proportion of short-chain FA but increased those of MUFA and PUFA. Increasing DIM reduced this proportion of short-chain FA and increased that of medium-chain FA. Higher SCC increased MAA.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".