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Record W2148800480 · doi:10.4141/cjas08040

Effect of dried distillers’ grains from wheat on diet digestibility and performance of feedlot cattle

2008· article· en· W2148800480 on OpenAlexvenueno aff
D. J. Gibb, Xiying Hao, Tim A. McAllister

Bibliographic record

VenueCanadian Journal of Animal Science · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsnot available
Fundersnot available
KeywordsDistillers grainsDry matterFeedlotSilageChemistryAnimal scienceFood scienceAgronomyBiology

Abstract

fetched live from OpenAlex

In a 55-d backgrounding period, 120 (n = 22) British cross heifers (312 ± 20 kg) received diets containing 55% barley silage, 5% supplement and 0 (n = 24), 20 (n = 24), or 40% (n = 22) wheat distillers’ dried grains with solubles (DDGS). The remainder of the diet was steam-rolled barley. Replacing half (20%) or all (40%) of the barley with DDGS did not affect dry matter intake (DMI) (P = 0.61), average daily gain (ADG) (P = 0.86), or gain:feed (P = 0.94), indicating the energy content of DDGS is similar to that of barley when included in backgrounding diets. During a 133-d finishing period, DDGS were included at 0, 20, 40, or 60% of diet dry matter (DM) or at 60% plus additional calcium, provided as 1% limestone (n = 24). Additional calcium did not (P > 0.1) affect DMI, ADG, or gain:feed. Increasing levels of DDGS linearly increased (P = 0.001) DMI and reduced (P = 0.04) gain:feed and diet NEg content (P = 0.001), but had no effect on ADG (P = 0.20). Feeding 60% DDGS reduced (P < 0.01) DM digestibility as compared with the control. Wheat DDGS has similar feeding value as barley when included at 20% of diet DM, but digestibility and energy content decline with higher levels of inclusion. Key words: Beef, digestibility, distillers' dried grains, wheat

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.619
Threshold uncertainty score0.676

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.021
GPT teacher head0.226
Teacher spread0.205 · 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 teacher head, 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

Citations98
Published2008
Admission routes1
Has abstractyes

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