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Record W2748253782 · doi:10.1002/047167849x.bio008

Fat Crystal Networks

2005· other· en· W2748253782 on OpenAlexaff
Geoffrey G. Rye, Jerrold W. Litwinenko, Alejandro G. Marangoni

Bibliographic record

VenueBailey's Industrial Oil and Fat Products · 2005
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicFood Chemistry and Fat Analysis
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsFractalNetwork structureIdentification (biology)Crystal structureMaterials scienceBiological systemMechanical strengthStatistical physicsComputer scienceMathematicsPhysicsCrystallographyComposite materialChemistryTheoretical computer scienceMathematical analysisBiology

Abstract

fetched live from OpenAlex

Abstract This paper reviews the identification of the various levels of structure present in milk fat crystal networks, and the development of analytical techniques to quantify these levels. The relationship of the various levels of structure to macroscopic physical indicators of the mechanical strength of the network is discussed. The analysis of the microstructural level of the network via fractal geometrical methods is outlined, as well as mechanical models relating the structure to mechanical properties. The effect of processing conditions on the different levels of structure and mechanical properties also 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)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.017
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0170.002

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 head0.027
GPT teacher head0.203
Teacher spread0.176 · 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
GenreOther

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

Citations113
Published2005
Admission routes1
Has abstractyes

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