Whole-tract dry matter and nitrogen digestibility of lactating dairy cows selected for phenotypic divergence in residual feed intake
Bibliographic record
Abstract
The objective of this experiment was to compare the whole-tract digestibility of dry matter (DM) and nitrogen (N) in Holstein-Friesian dairy cows selected for divergent feed conversion efficiency. The experiment used 16 primiparous Holstein–Friesian dairy cows selected based on their residual feed intake (RFI) measured as growing calves. The cows were housed in individual metabolism stalls and fed lucerne cubes ad libitum plus 6 kg DM per day of crushed wheat grain. Feed intake, milk yield, faecal and urine output were measured for 5 days. Rumen fluid was collected per os from each cow on one occasion. Milk production parameters and intakes of DM, organic matter, neutral detergent fibre, acid detergent fibre and N did not differ between RFI groups. Apparent whole-tract DM digestibility and N digestibility did not differ between RFI treatment groups. Rumen metabolites were also unaffected by RFI. In conclusion, divergence in RFI as calves was not associated with differences in whole-tract DM or N digestibility in lactating cows. Therefore, emphasis on selection for phenotypic divergence in RFI may not contribute to improved utilisation of consumed nutrients in Australian Holstein-Friesian dairy cows.
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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 | 0.000 | 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 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".