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Record W2031392755 · doi:10.1002/jsfa.2073

Fatty acid and nitrogen utilization of processed flaxseed by adult chickens

2005· article· en· W2031392755 on OpenAlexafffund
Yingran Shen, Dingyuan Feng, T. F. Oresanya, Eduardo R. Chávez

Bibliographic record

VenueJournal of the Science of Food and Agriculture · 2005
Typearticle
Languageen
FieldMedicine
TopicPhytoestrogen effects and research
Canadian institutionsMcGill UniversityUniversity of SaskatchewanUniversity of Guelph
FundersMcGill University
KeywordsRoastingIngredientChemistryCanolaFood scienceFatty acidNitrogenBiochemistry

Abstract

fetched live from OpenAlex

Abstract The effect of flaxseed processing on the utilization of fatty acids and nitrogen were examined in adult chicken. Two batches (A and B) of flaxseed were processed by autoclaving, pelleting, or microwave roasting. Thirty grams of the ground ingredient was given to fasted Leghorn roosters. The apparent digestibility of total fatty acids of raw flaxseeds A and B were 660 and 490 g kg−1, respectively. Its improvement (p < 0.05) reached 29% for flaxseed A after three‐times repeated pelleting. Similarly, it was 39% (p < 0.05) for flaxseed B after 4 min of microwave roasting. The improvement in the absorption of major individual fatty acids in flaxseed followed the same pattern as that of total fatty acids. The apparent digestibility of linolenic acid in extruded full‐fat soybean was much higher (p < 0.05) than that in raw flaxseed A, but not that in processed flaxseed A (p > 0.05). Furthermore, roosters given canola seed had significantly higher true nitrogen utilization (p < 0.05) than those fed raw flaxseed A. This difference was reduced or non‐existent (p > 0.05) with processed flaxseed. Proper flaxseed processing effectively increases the utilization of major fatty acids and nitrogen in flaxseed for adult chicken. Copyright © 2005 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 score0.002
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 head0.011
GPT teacher head0.264
Teacher spread0.253 · 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

Citations17
Published2005
Admission routes2
Has abstractyes

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