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Record W7056178390

Effects of barley based diets with three different rumen degradable protein balances on performance and carcass characteristics of feedlot steers

2013· other· en· W7056178390 on OpenAlexfundno aff

Bibliographic record

Venuenot available
Typeother
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
FundersBeef Cattle Research Council
KeywordsRumenFeedlotCarcass weightDigestion (alchemy)Animal production
DOInot available

Abstract

fetched live from OpenAlex

The objective of this study was to determine the effect of dietary optimal or suboptimal rumen available protein to energy ratios generated by substituting barley grain by wheat –based dried distillers’ grains with soluble (wDDGS) on finishing feedlot cattle performance. Three hundred crossbred steers were randomly assigned to twelve pens (25 heads in each pen) and fed one of three grain based finishing diets with: (i) negative rumen degradable protein balance (DPB; -12 g/kg DM); (ii) neutral DPB (0 g/kg DM); and (iii) positive DPB (14 g/kg DM). Ration with negative DPB (conventional feed) contained 88.3% rolled barley grain, 7.0% supplement and 4.7% barley silage. For the rations with neutral - and positive DPB, the barley grain was replaced by wDDGS at 11 or 22% of the diet, respectively. Over the 131-d finishing period, animal performance and carcass traits were similar among steers fed either of 3 finishing diets. In conclusion, barley grain in common feedlot diets can be substituted by wDDGS up to 22%, without altering steer performance and carcass characteristics.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.004
GPT teacher head0.188
Teacher spread0.183 · 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 designBench or experimental
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

Citations0
Published2013
Admission routes1
Has abstractyes

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