A model of milk production in lactating dairy cows in relation to energy and nitrogen dynamics
Bibliographic record
Abstract
A generic daily time-step model of a dairy cow, designed to be included in whole-system pasture simulation models, is described that includes growth, milk production, and lactation in relation to energy and nitrogen dynamics. It is a development of a previously described animal growth and metabolism model that describes animal body composition in terms of protein, water, and fat, and energy dynamics in relation to growth requirements, resynthesis of degraded protein, and animal activity. This is further developed to include lactation and fetal growth. Intake is calculated in relation to stage of lactation, pasture availability, supplementary feed, and feed quality. Energy costs associated with urine N excretion and methane fermentation are accounted for. Milk production and fetal growth are then calculated in relation to the overall energy and nitrogen dynamics. The general behavior of the model is consistent with expected characteristics. Simulations using the model as part of a whole-system pasture simulation model (DairyMod) are compared with experimental data where good agreement between pasture, concentrate and forage intake, as well as milk production over 3 consecutive lactation cycles, is observed. The model is shown to be well suited for inclusion in large-scale system simulation models.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".