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Record W2047209061 · doi:10.1002/jsfa.1677

Effect of flaxseed processing on its true metabolizable energy values for adult chicken

2004· article· en· W2047209061 on OpenAlexafffund
Yingran Shen, Dingyuan Feng, Eduardo R. Chávez

Bibliographic record

VenueJournal of the Science of Food and Agriculture · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsMcGill UniversityUniversity of Guelph
FundersMcGill University
KeywordsRoastingChemistryDry matterFood scienceAnimal scienceBiology

Abstract

fetched live from OpenAlex

Abstract The objective of the present experiment was to study the effect of flaxseed processing on nitrogen corrected true metabolizable energy (TMEn) values for adult roosters. Flaxseed was processed as pelleted, autoclaved or microwave roasted. Leghorn roosters were used for the TME determination procedure. The TMEn value of flaxseed batch A, 14.48 MJ kg−1 DM, was significantly (P < 0.05) increased to 17.89 MJ kg−1 DM by three‐time repeat‐pelleting, or to 18.07 MJ kg−1 dry matter (DM) by autoclaving, respectively. Microwave roasting also significantly (P < 0.05) increased the TMEn value of flaxseed batch B by 22%. The TMEn improvement observed due to processing was accompanied by increased ether extract utilization. The apparent ether extract digestibility of flaxseed batch A, 61.2%, was very significantly (P < 0.01) increased to 81.5 and 83.2% by processing as repeat‐pelleting and autoclaving, respectively. Microwave roasting also significantly (P < 0.05) increased the apparent digestibility of ether extract for flaxseed batch B from 49.1 to 64.4%. Proper flaxseed processing as pelleting, autoclaving and microwave roasting led to higher TMEn values for Leghorn roosters, mainly as the result of increased ether extract utilization. Copyright © 2004 Society of Chemical Industry

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 score0.001
Threshold uncertainty score0.004

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 communication0.0000.000
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 head0.010
GPT teacher head0.227
Teacher spread0.217 · 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

Citations4
Published2004
Admission routes2
Has abstractyes

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