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PARTICLE SIZE EFFECT ON SOY PROTEIN ISOLATE EXTRACTION

2007· article· en· W2098684826 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 Food Processing and Preservation · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPhytase and its Applications
Canadian institutionsAgriculture and Agri-Food Canada
FundersNational Institute of Environmental Health Sciences
KeywordsSoy proteinSoy flourParticle sizeRaw materialFood scienceChemistryExtraction (chemistry)High proteinParticle (ecology)ChromatographyBiology

Abstract

fetched live from OpenAlex

This study was undertaken to determine if the yield and purity of soy protein isolates could be improved by changing the particle size of the starting raw material. Soy protein isolates were extracted from hexane defatted soy flour ground to three different average particle sizes (89.5 ± 1.1, 184.2 ± 1.6 and 223.4 ± 6.4 µm). By decreasing the average particle diameter of the starting raw material (soy flour) from 223.4 to 89.5 µm the total solids recovery increased from 23 to 32% (P = 0.00008), while the protein recovery increased from 40 to 52% (P = 0.00004). Final protein content (i.e., purity) of the soy protein isolates was not significantly impacted by average particle size. The results clearly demonstrated that protein recovery can be increased by >30% by decreasing the average particle size of the starting raw material (i.e., defatted soy flour), without having any detrimental impact on the purity of the final soy protein isolate.

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)0.000
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 score0.417
Threshold uncertainty score0.123

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.026
GPT teacher head0.272
Teacher spread0.246 · 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