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Effects of Forage Source and Amount of Concentrate on Rumen and Intestinal Digestion of Nutrients in Late-Lactation Cows

2001· article· en· W1990325418 on OpenAlexaff
G.R. Khorasani, E. K. Okine, J.J. Kennelly

Bibliographic record

VenueJournal of Dairy Science · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsForageRumenDry matterDigestion (alchemy)Latin squareSilageNutrientAgronomyBiologyAnimal scienceFodderLactationChemistryFood scienceFermentation

Abstract

fetched live from OpenAlex

The objectives of this study were to determine the effects of dietary forage source with two concentrate concentrations on dry matter (DM) intake, rumen fill, ruminal and intestinal digestibility of nutrients, and duodenal N fractions in lactating cows. Four rumen and duodenal cannulated Holstein cows in late lactation were used in 4 x 4 Latin square design experiment with 21-d periods. Diets were 1) 65% first-cut alfalfa silage and 35% concentrate, 2) 50% alfalfa and 50% concentrate, 3) 65% bromegrass silage and 35% concentrate, and 4) 50% bromegrass and 50% concentrate. Dry matter intake was not affected by forage source but tended to be (P = 0.08) higher for cows fed diets with 50% concentrate. Rumen fill was greater (P < 0.01) for cows fed bromegrass compared with those fed alfalfa silage. Ruminal and intestinal digestion of DM was not affected by dietary forage source or concentrate level. Total N intake was greater for cows fed alfalfa-based diets, reflecting the higher crude protein content of alfalfa. However, total N flow at the duodenum was not affected by either forage source or concentrate in the diet. Although forage source influenced the site of digestion of some nutrients no significant effects on total tract digestibilities were observed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.236
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations35
Published2001
Admission routes1
Has abstractyes

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