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Record W2045769234 · doi:10.1021/jf010303s

Study of Soybean Seed Coat Components and Their Relationship to Water Absorption

2001· article· en· W2045769234 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 Agricultural and Food Chemistry · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoybean genetics and cultivation
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsAbsorption of waterHemicellulosePolysaccharideCoatLigninFood scienceAgronomyAbsorption (acoustics)ChemistryXylanWater contentBotanyBiologyBiochemistry

Abstract

fetched live from OpenAlex

The occurrence of hard or "stone" seeds in shipments of food grade soybeans can cause serious problems in processing, particularly in the preparation of fermented soy products. Climatic conditions during the growing season and as the seed matures may trigger the production of hard seeds. Total water absorption of soybeans is also a significant parameter in assessing quality for export markets. The seed coats of six varieties of soybeans, covering a wide range of water absorption and stone seed content, were analyzed for ash and cations, protein, lignin, and complex carbohydrates. The water absorption characteristics and macrochemical constituents of the whole seed were also determined. The results indicated that there was no correlation between the concentration of any of the cations and the occurrence of hard seeds. The results from analysis of the complex carbohydrates indicated there were differences in hemicellulose content of seed coat fractions, particularly xylans, that correlated with the water uptake ratio and the occurrence of hard seeds.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.839
Threshold uncertainty score0.103

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 head0.031
GPT teacher head0.208
Teacher spread0.178 · 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