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Record W4399878206 · doi:10.3136/fstr.fstr-d-24-00067

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

2024· article· en· W4399878206 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

VenueFood Science and Technology Research · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGABA and Rice Research
Canadian institutionsConestoga Meat Packers (Canada)
Fundersnot available
KeywordsAminobutyric acidHydrostatic pressureChemistryKinetic energygamma-Aminobutyric acidHydrostatic equilibriumFood scienceBiochemistryThermodynamicsPhysics

Abstract

fetched live from OpenAlex

We aimed to investigate the effect of high hydrostatic pressure (HHP) on the production of amino acids, including GABA, in buckwheat during preservation. Buckwheat was soaked in 0–0.5 % glutamic acid solution and exposed to HHP treatment at 200 or 400 MPa. The concentrations of amino acids, except glutamic acid, increased with HHP treatment and preservation. GABA production tended to be higher in a 0.3 g/mL Glu solution under 400 MPa. The relationship between initial glutamate concentration and GABA production rate was bell-shaped, with a maximum approximately 50 µmol/g for the 200-MPa and untreated samples. The Km, Ki, and Vmax were calculated from the Michaelis–Menten equation with substrate inhibition. The Km changed after 400-MPa HHP treatment, whereas Vmax and Ki increased in a pressure-dependent manner. Combining Glu and HHP treatment can produce buckwheat with enhanced GABA production.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
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 score0.844
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.021
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.028
GPT teacher head0.308
Teacher spread0.279 · 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