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Record W2090169027 · doi:10.1016/j.jff.2008.09.013

Tracking isoflavones: From soybean to soy flour, soy protein isolates to functional soy bread

2008· article· es· W2090169027 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Functional Foods · 2008
Typearticle
Languagees
FieldMedicine
TopicPhytoestrogen effects and research
Canadian institutionsUniversity of GuelphAgriculture and Agri-Food Canada
Fundersnot available
KeywordsIsoflavonesSoy proteinFood scienceSoy flourChemistrySoy milkComposition (language)Soy beanSOY ISOFLAVONESBiochemistry

Abstract

fetched live from OpenAlex

Soybean seeds with three different levels (low, intermediate and high) of isoflavones were processed to soy flour and soy protein isolates (SPIs) and developed into functional soy breads. The effect of factors involved in all steps of the process was investigated by tracking the composition and concentration of native forms of isoflavones. The total isoflavone contents were 8033.3, 10570.1 and 15169.0 nmol/g DM (dry matter) in the three soybeans; 13201.5, 20034.4 and 26014.3 nmol/g DM in defatted soy flours; 9113.2, 13274.6 and 17918.3 nmol/g DM in the SPI; 2782.7, 4081.4 and 5590.3 nmol/g DM in soy breads, respectively. The bread making processes did not affect the total isoflavone content, but changed glucosides/acetylglucosides to aglycones. Malonylglucosides were stable prior to baking but degraded to acetylglucosides and further to glucosides during baking. Our results provide critical information for the production of functional soy breads that contain varying amounts of soy isoflavones.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.716
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.306
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