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Record W2015581831 · doi:10.1016/j.lwt.2010.08.007

Effect of acid hydrolysis on rheological and thermal characteristics of lentil starch slurry

2010· article· en· W2015581831 on OpenAlex
Jasim Ahmed, Rafael Auras

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

VenueLWT · 2010
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsPolymer Source (Canada)
Fundersnot available
KeywordsStarchHydrolysisRheologyStarch gelatinizationCreepSlurryAcid hydrolysisChemistryChemical engineeringIsothermal processKineticsMaterials scienceActivation energyEnthalpyComposite materialOrganic chemistryThermodynamics

Abstract

fetched live from OpenAlex

A comparative rheological and thermal study was carried out between acid hydrolyzed and unhydrolyzed (control) lentil starch dispersions (25–33.3 g starch per 100 g water) as function of temperature. After acid hydrolysis, the peak gelatinization temperature (Tp) shifted to higher temperature than the corresponding starch without hydrolysis whereas the gelatinization enthalpy remained unaffected by hydrolysis. The starch gelatinization kinetics was evaluated by a non-isothermal technique as function of elastic modulus (G′) and G′ vs. time (t) data up to the gelatinization peak value was considered for rate estimation. A 2nd-order reaction kinetics described well the starch gelatinization process and the process activation energy was ranged between 241 and 434 kJ/mol. Acid hydrolysis strongly affected the rheological properties by lowering gel strength compared to unhydrolyzed starch. The creep analysis further revealed that starch gel was significantly affected by hydrolysis and exhibited less resistant to the stress. A 4-parameters Burgers model well-described creep curves and supported oscillatory rheological data.

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 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 score0.075
Threshold uncertainty score0.184

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 head0.009
GPT teacher head0.247
Teacher spread0.238 · 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