Simulation analysis of substrate utilization in the mammary gland of lactating cows
Bibliographic record
Abstract
A kinetic modelling approach was developed and investigated with the aim of predicting the utilization of major substrates in the mammary gland and milk secretion rates in the lactating cow at varying concentrations of substrate in arterial blood. The model includes kinetic equations of transport and metabolism of glucose, acetate, free amino acids and free fatty acids in secretory cells and a phenomenological description of autoregulation of local blood flow, in which an energy criterion of control has been used. The predicted relationships between the rate of milk secretion and glucose levels in the blood are consistent with experimental results. Differential stimulation of alpha-lactalbumin synthesis causes increments in local blood flow and milk secretion rate in the model. The results of the study suggest that there is no simple relationship between the level of substrates in the blood and milk yield and contents of fat and protein in milk. This is because the effect on production of varying patterns of substrate concentrations in the blood is mediated by network interactions at the level of secretory cell metabolism and microcirculation. However, dynamic modelling provides a rational framework for developing such predictive tools.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".