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Record W2049240677 · doi:10.1002/star.200600547

Physical Aging of Amorphous Starches (A Review)

2006· article· en· W2049240677 on OpenAlexaff
Hyun‐Jung Chung, Seung‐Taik Lim

Bibliographic record

VenueStarch - Stärke · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMicroencapsulation and Drying Processes
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsAmorphous solidMaterials scienceRelaxation (psychology)Food scienceGlass transitionStarchChemistryPolymerPsychologyComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract In recent years, physical behaviors of glassy foods are greatly focused as many processed foods are consumed in their glassy states. Physical aging is one of the important phenomena for glassy foods, which is responsible for quality changes vs. retention of freshness during storage. The aging phenomenon can be predicted on the basis of a process of thermodynamic relaxation, induced by structural rearrangements in amorphous matrices. Thus, it can be evaluated by using calorimetric, volumetric, and mechanical analyses. Starch is one of the principal components in most cereal‐based glassy foods, and its aging is thus relevant to the overall changes in quality and freshness of various cereal‐based food products. The polymeric theory for the physical aging of glassy starch is reviewed on the basis of the existing literature, and the aging kinetics based on the changes in various physical and thermal properties are discussed.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.019
GPT teacher head0.253
Teacher spread0.234 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations29
Published2006
Admission routes1
Has abstractyes

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