MétaCan
Menu
Back to cohort
Record W2321782838 · doi:10.1021/jf501284a

Molecular Structures and Metabolic Characteristics of Protein in Brown and Yellow Flaxseed with Altered Nutrient Traits

2014· article· en· W2321782838 on OpenAlexaff
Nazir Ahmad Khan, Helen Booker, Peiqiang Yu

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2014
Typearticle
Languageen
FieldMedicine
TopicPhytoestrogen effects and research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsNutrientBiologyEcology

Abstract

fetched live from OpenAlex

The objectives of this study were to investigate the chemical profiles; crude protein (CP) subfractions; ruminal CP degradation characteristics and intestinal digestibility of rumen undegraded protein (RUP); and protein molecular structures using molecular spectroscopy of newly developed yellow-seeded flax (Linum usitatissimum L.). Seeds from two yellow flaxseed breeding lines and two brown flaxseed varieties were evaluated. The yellow-seeded lines had higher (P < 0.001) contents of oil (44.54 vs 41.42% dry matter (DM)) and CP (24.94 vs 20.91% DM) compared to those of the brown-seeded varieties. The CP in yellow seeds contained lower (P < 0.01) contents of true protein subfraction (81.31 vs 92.71% CP) and more (P < 0.001) extensively degraded (70.8 vs 64.9% CP) in rumen resulting in lower (P < 0.001) content of RUP (29.2 vs 35.1% CP) than that in the brown-seeded varieties. However, the total supply of digestible RUP was not significantly different between the two seed types. Regression equations based on protein molecular structural features gave relatively good estimation for the contents of CP (R(2) = 0.87), soluble CP (R(2) = 0.92), RUP (R(2) = 0.97), and intestinal digestibility of RUP (R(2) = 0.71). In conclusion, molecular spectroscopy can be used to rapidly characterize feed protein molecular structures and predict their nutritive value.

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: Observational · Consensus signal: none
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 communication0.0000.000
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 head0.005
GPT teacher head0.210
Teacher spread0.204 · 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 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

Citations30
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Agricultural and Food ChemistrySame topicPhytoestrogen effects and researchFrench-language works237,207