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Record W2035474958 · doi:10.1021/bp000001v

Effect of Temperature on the Separation of Soybean 11 S and 7 S Protein Fractions during Bipolar Membrane Electroacidification

2000· article· en· W2035474958 on OpenAlex
Laurent Bazinet, Denis Ippersiel, Raynald Labrecque, F. Lamarche

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

VenueBiotechnology Progress · 2000
Typearticle
Languageen
FieldEngineering
TopicMembrane-based Ion Separation Techniques
Canadian institutionsHydro-QuébecAgriculture and Agri-Food Canada
Fundersnot available
KeywordsSeparation (statistics)ChromatographyChemistryMembraneBiochemistryMathematicsStatistics

Abstract

fetched live from OpenAlex

The purpose of this study was to evaluate the effect of temperature (10 and 27 degrees C) on the efficiency of bipolar membrane electroacidification (BMEA) to fractionate soybean proteins. BMEA is a technology derived from electrodialysis, based on the isoelectric precipitation of proteins. It appears that temperature has a significant effect on the selective precipitation of the soybean protein fractions, mainly 11 S and 7 S, during BMEA. At 27 degrees C, the precipitation profile of the four protein fractions is situated in a pH range from 6.6 to 4.4, with no possibility of separating any of theses fractions. However, at 10 degrees C, the 11 S globulin precipitates at a higher pH than at 27 degrees C, pH 6.7 vs 5.9, allowing the fractionation of 11 S from the other fractions. Using electroacidification it is possible to obtain a precipitate solution enriched in the 11 S fraction (71.8% of 11 S and 10.8% of 7 S) and a supernatant solution enriched in the 7 S fraction (46.6% of 7 S and 4.6% of 11S).

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.484

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 head0.005
GPT teacher head0.242
Teacher spread0.237 · 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