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Record W2061705615 · doi:10.1063/1.2769143

Large deformation analysis of gellan gels

2007· article· en· W2061705615 on OpenAlex
Shinnosuke Kawai, Yoko Nitta, Katsuyoshi Nishinari

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

VenueJournal of Applied Physics · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPolysaccharides Composition and Applications
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsSofteningHardening (computing)Materials scienceStrain hardening exponentComposite materialGellan gumGelatinDeformation (meteorology)Chemistry

Abstract

fetched live from OpenAlex

Gellan gel, a typical polysaccharide gel, is ruptured with different deformation behaviors from gelatin gel or rubber. It exhibits both strain hardening and softening; hardening is observed for moderate strain and softening occurs for larger strain. From the analyses of stress–strain curves of gellan gels, we propose forms of strain energy function. The fit with the proposed equation was excellent, while the existing models fail because they consider only one of hardening or softening effect. Furthermore, these equations are shown to be capable of extracting the hardening and softening effects separately from the observed stress–strain curves. By using these fitting equations, the concentration dependences of hardening and softening are investigated. It is shown that the degrees of hardening and softening both increase with increasing gellan concentration.

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 score0.224
Threshold uncertainty score0.081

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.016
GPT teacher head0.242
Teacher spread0.227 · 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