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Record W3119294462 · doi:10.14674/ijfs-1290

AN INVESTIGATION OF THE MECHANICAL, MICROSTRUCTURAL AND THERMO-MECHANICAL PROPERTIES OF COLLAGEN FILMS CROSS-LINKED WITH SMOKE CONDENSATE AND GLUTARALDEHYDE

2019· article· en· W3119294462 on OpenAlexaff
Shai Barbut, M. Ioi

Bibliographic record

VenueItalian Journal of Food Science · 2019
Typearticle
Languageen
FieldMaterials Science
TopicCollagen: Extraction and Characterization
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsGlutaraldehydeElongationUltimate tensile strengthMaterials scienceOpacityTransmission electron microscopyComposite materialExtrusionChemical engineeringChemistryChromatographyNanotechnologyOptics

Abstract

fetched live from OpenAlex

Collagen films were produced from five commercial collagen dispersions used for in-line sausage co-extrusion production. Films were prepared by partially dehydrating in a salt solution (30%) and crossed linked with smoke condensate (15%) or glutaraldehyde (GA; 0-1%). Both treatments increased the tensile strength (0.32 to 0.91 MPa) and reduced % elongation while differences among the dispersions were observed. Overall, % elongation generally decreased with a higher degree of cross linking. Transmission electron micrographs revealed that collagen fibers were swollen to varying degrees, likely influencing the mechanical behaviours. Protein concentration affected the transparency of the films with a difference of 100% in light transmission between the clearest and most opaque film studied. Cross-linking with GA appeared to thermally stabilize films up to 800C. Aldehydes in the smoke condensate were identified by gas chromatography showing highest concentration of benzaldehyde, 4-hydroxy-3,5-dimethoxy.

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)0.001
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 score0.082
Threshold uncertainty score0.323

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.021
GPT teacher head0.246
Teacher spread0.225 · 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

Citations12
Published2019
Admission routes1
Has abstractyes

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