Development of an efficiency ranking system for beef cows and effects on feed intake, ruminal fermentation, NDF turnover, and apparent total tract digestibility
Bibliographic record
Abstract
Beef cows ( n = 100) were ranked for efficiency based on cow rump fat thickness at calving, calving date, and calf weaning weight (% dam BW) over 2 years. The nine most (ME) and least efficient (LE) cows were used to compare feed intake and ruminal fermentation using four 26-day periods with decreasing dietary nutrient density. There were no phenotype × diet interactions for variables of primary interest. Rump fat and calf weaning weight were greater, and the calving date was earlier for ME cows than LE cows ( P ≤ 0.032). The ME cows were lighter ( P < 0.001) but had similar DMI ( P = 0.93) to the LE cows, resulting in greater dry matter intake (DMI) %BW ( P < 0.001). Ruminal contraction amplitude height and area ( P ≤ 0.015) and ruminal digesta weight were greater for LE than ME cows ( P = 0.043). Ruminal ash-free neutral detergent fiber (aNDFom) passage was greater for ME cows than LE cows ( P = 0.047), but the rate of aNDFom degradation did not differ ( P = 0.69). Total tract digestibility did not differ. Efficient cows had greater rump fat, weaned heavier calves, ate more relative to their BW, had a smaller ruminal digesta mass, and had greater ruminal passage of aNDFom without reducing digestibility.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".