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Record W2157189366 · doi:10.5539/jfr.v3n6p188

Soybean Seed Coats: A Source of Ingredients for Potential Human Health Benefits-A Review of the Literature

2014· article· en· W2157189366 on OpenAlexvenueno aff
Corliss A. O’Bryan, Kalpana Kushwaha, D. R. C. Babu, Philip G. Crandall, Mike L. Davis, Pengyin Chen, Sun‐Ok Lee, Steven C. Ricke

Bibliographic record

VenueJournal of Food Research · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoybean genetics and cultivation
Canadian institutionsnot available
FundersAgricultural Marketing Service
KeywordsBushelHealth benefitsSoybean oilHuman healthFood scienceObesityBiologyBiotechnologyHorticultureAgronomyMedicineTraditional medicineEnvironmental health

Abstract

fetched live from OpenAlex

<p>Soybean seed coats are an underutilized byproduct from the commercial crushing of soybeans to make soymeal and soy oil. These seed coats constitute 7 to 10% of the weight of a bushel of soybeans so they provide a substantial opportunity to add value to each bushel. Overall, the United States produces approximately 6 million metric tons of seed coats each year. Biologically active compounds contained in soybean seed coats have been shown to prevent and or reduce macular degeneration, obesity, cancer, and many other debilitating diseases. For example the seed coats of YJ-100 black soybeans contain more than 20 mg/g of anthocyanins, the highest concentration of anthocyanins of all plants materials including other row crops. The purpose of this paper is to examine the chemical content of soybean seed coats, highlight opportunities to add value and discuss the potential health benefits of these chemicals.</p>

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.705
Threshold uncertainty score0.150

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.067
GPT teacher head0.336
Teacher spread0.269 · 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.

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

Citations12
Published2014
Admission routes1
Has abstractyes

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