Effects of dietary supplement sources on the rate and extent of in vitro ruminal degradation of alfalfa-based diets for cattle
Bibliographic record
Abstract
Two ruminally cannulated steers [928 ± 25.5 kg body weight (BW)] were fed alfalfa hay at 2.0% of BW and served as donors of rumen fluid. Treatments were early-bud alfalfa (CON) or a combination [dry matter (DM) basis] of 80% early-bud alfalfa with 20% of corn silage (CS), brome grass hay (BGH), soybean hulls (SBH), beet pulp (BP), corn grain (CORN), dried corn distillers’ grains with solubles (DDGS), or wheat middlings (MIDD). Tubes were incubated at multiple time points over a 72 h period and assessed for rate and extent of digestion. Samples were run in duplicate and replicated over 3 d. The potential extent of DM and organic matter (OM) degradation increased (P < 0.001) with CS, SBH, BP, CORN, and DDGS supplementation compared with CON. All supplements except MIDD decreased (P < 0.001) the fractional rates of DM and OM degradation compared with CON, with BGH, SBH, and DDGS having the lowest rates. Supplementation of SBH had the lowest (P < 0.001) initial rate of DM and OM degradation. These data indicate that SBH increases the extent of digestion while reducing the initial rate of degradation, suggesting that SBH has potential to reduce the incidence of frothy legume bloat.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".