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Record W2005344047 · doi:10.1021/jf063045d

Thermal Denaturation and Aggregation Properties of Atlantic Salmon Myofibrils and Myosin from White and Red Muscles

2007· article· en· W2005344047 on OpenAlexaff
Florence Lefèvre, Benoı̂t Fauconneau, John W. Thompson, Tom Gill

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMyofibrilMyosinDenaturation (fissile materials)ChemistryBiophysicsMeromyosinBiochemistryMyosin headMyosin light-chain kinaseBiologyNuclear chemistry

Abstract

fetched live from OpenAlex

Thermal denaturation and aggregation abilities of salmon myofibrils and myosin were studied measuring turbidity, intrinsic fluorescence, 8-anilino-1-naphthalene sulfonic acid binding, and 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide cross-linking. The thermal behaviors of protein preparation from white and red muscles were compared, and the relationship with thermal gelation properties is discussed. The low gelation ability of salmon muscle proteins was related to a limited extent of protein denaturation and aggregation upon heating. These properties seemed to be carried by myosin molecules as a similar behavior was observed for both myofibrils and myosin preparations. The higher thermal stability observed for red muscle proteins with higher transition temperatures in rheological profiles was related to a shift to higher temperature in denaturation and aggregation processes. The extent of denaturation and aggregation was very similar for both muscle types as was the final rigidity of the gels formed.

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 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.572
Threshold uncertainty score0.142

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 head0.020
GPT teacher head0.195
Teacher spread0.175 · 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 teacher head, 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

Citations100
Published2007
Admission routes1
Has abstractyes

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