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Record W2315874297 · doi:10.1055/s-0033-1336503

Isoflavones Derived from Soy, Red Clover, and Kudzu in Safety Assessments: Identity, Form, Quantity, and Product Matrix Considerations

2013· article· en· W2315874297 on OpenAlexaff
M Steller, S Jogalekar, Alice H. Smith, Robin J. Marles

Bibliographic record

VenuePlanta Medica · 2013
Typearticle
Languageen
FieldMedicine
TopicPhytoestrogen effects and research
Canadian institutionsHealth Canada
Fundersnot available
KeywordsIsoflavonesKudzuAglyconePuerarinDaidzinContext (archaeology)Food scienceChemistryMedicineBiotechnologyBiochemistryBiologyGlycosideStereochemistryDaidzeinEndocrinologyGenistein

Abstract

fetched live from OpenAlex

Assessing the safety of botanicals containing isoflavones hinges primarily upon their potential to elicit effects on estrogen metabolism, but this assessment can only be reliably conducted with adequate characterization of the isoflavones involved. Of particular relevance to the regulatory context are soy (Glycine max), red clover (Trifolium pratense), and kudzu (Pueraria montana). Each of these species can contain variable quantities and congeners of isoflavones, rendering the consistent preparation of these products critical to quality control and, ultimately, safety and efficacy. Aglycone forms of the isoflavones have generally been regarded as more readily absorbable than their glycosidic counterparts. However, glycosidic forms of certain isoflavones, such as puerarin, can also be absorbed to a significant extent, so when they are present, safety should be assessed using glycosidic isoflavone amounts rather than the conventional aglycone equivalents. To complicate matters, absorption rates for the isoflavones can also be affected by the product's matrix, suggesting that the isoflavones may also be absorbed by other means than simply passive diffusion. Thus, thoroughly assessing the safety profile of a given isoflavone preparation requires detailed characterization of the product as a whole and the product's recommended conditions of use. Nevertheless, in the absence of this product specific characterization, limited inferences from the broader data can also be applied to appropriately address uncertainties and mitigate the potential for risk.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.159
Threshold uncertainty score0.593

Codex and Gemma teacher scores by category

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 head0.029
GPT teacher head0.355
Teacher spread0.326 · 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 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

Citations2
Published2013
Admission routes1
Has abstractyes

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