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Record W7010188221

Grain processing differences between barley varieties for cattle

2005· other· en· W7010188221 on OpenAlexaffabout

Bibliographic record

Venuenot available
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Health
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsCultivarGrain yieldFood processingHordeum vulgareStatistical analysis
DOInot available

Abstract

fetched live from OpenAlex

Barley is fed to cattle as a concentrated energy source. Before feeding, the grain is cracked (processed) to expose the endosperm to rumen fermentation. Processing disrupts the endosperm starch-protein matrix and produces fine particles (fines). Fines may lead to acidosis and liver abscesses in cattle. In 2004, nine Western Canadian barley varieties, including seven feed and two malt varieties, were analyzed for fines produced after three processing treatments: dry with minimal processing, dry with excessive processing, and tempered with excessive processing. Fines were measured as the percentage of processed sample falling through a 1.40 mm brass sieve. Grain hardness, using Single Kernel Characterization System (SKCS), and protein content, using Near Infrared Transmittance (NIT) were analyzed to identify their relationship
\nwith fines production. Varieties differed in % fines produced after rolling with variety by processing interaction being present (P<0.05). However, Xena and CDC Dolly produced significantly less fines for all processing methods and CDC Trey and CDC Bold produced more (P<0.05). Varieties with more protein produced fewer fines when minimally dry rolled, with the exception of Xena (P<0.05). Grain hardness and protein content appear related to processing characteristics; however, correlations were not significant. Grain hardness was significantly correlated with protein (R=0.77, P<0.05).

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.155
Threshold uncertainty score0.991

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.000

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 head0.053
GPT teacher head0.278
Teacher spread0.225 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2005
Admission routes2
Has abstractyes

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