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Record W7077076441 · doi:10.3136/aamjsfst.71.0_362

The kinetic analysis of γ-aminobutyric acid (GABA) production in buckwheat after high hydrostatic pressure

2024· article· en· W7077076441 on OpenAlexaff

Bibliographic record

Venue日本食品科学工学会大会講演要旨集 = · 2024
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsConestoga Meat Packers (Canada)
Fundersnot available
KeywordsKinetic energyHydrostatic pressureProduction (economics)Atmospheric pressure

Abstract

fetched live from OpenAlex

【目的】200~400MPaの高圧処理は,一般に細胞組織を破壊するが,高分子成分には大きな影響を与えない.近年,生物素材に高圧処理を施すことで,膜構造や細胞組織が破壊され,内部での物質移動が促進したり酵素反応が加速したりするHi-Pit効果が注目されている.そして,Hi-Pit効果を活用してグルタミン酸脱炭酸酵素(GAD)の基質であるGluの供給と高圧処理を組み合わせ,農産物にγ-アミノ酪酸(GABA)を高含有させる技術開発が進められている.本研究では,ソバの実を対象とし,GABA生成反応に関して速度論的解析を行い,GABAを富化させる条件について実験的に検討した.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.016

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.006
GPT teacher head0.210
Teacher spread0.204 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2024
Admission routes1
Has abstractyes

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