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Record W1968991883 · doi:10.3390/biom3010168

Soybean Hydrophobic Protein Response to External Electric Field: A Molecular Modeling Approach

2013· article· en· W1968991883 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBiomolecules · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMagnetic and Electromagnetic Effects
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsElectric fieldMolecular dynamicsChemical physicsMaterials scienceElectromagnetic fieldField (mathematics)Protein structureAccessible surface areaBiological systemChemistryBiophysicsNanotechnologyPhysicsComputational chemistryBiologyBiochemistryMathematics

Abstract

fetched live from OpenAlex

The molecular dynamic (MD) modeling approach was applied to evaluate the effect of an external electric field on soybean hydrophobic protein and surface properties. Nominal electric field strengths of 0.002 V/nm and 0.004 V/nm had no major effect on the structure and surface properties of the protein isolate but the higher electric field strength of 3 V/nm significantly affected the protein conformation and solvent accessible surface area. The response of protein isolate to various external field stresses demonstrated that it is necessary to gain insight into protein dynamics under electromagnetic fields in order to be able to develop the techniques utilizing them for food processing and other biological applications.

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 categoriesMeta-epidemiology (narrow)
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 score0.104
Threshold uncertainty score1.000

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 head0.004
GPT teacher head0.218
Teacher spread0.213 · 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