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Record W2036588822 · doi:10.1007/s11746-000-0194-2

Comparison of experimental techniques used in lipid crystallization studies

2000· article· en· W2036588822 on OpenAlexaff
Amanda J. Wright, Suresh S. Narine, Alejandro G. Marangoni

Bibliographic record

VenueJournal of the American Oil Chemists Society · 2000
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Chemistry and Fat Analysis
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsCrystallizationTurbidimetryPolarized light microscopyMicroscopyAnhydrousLight scatteringMaterials scienceChromatographyAnalytical Chemistry (journal)ChemistryTurbidityScatteringOpticsPhysicsBiology

Abstract

fetched live from OpenAlex

Abstract Four methods were used to monitor the crystallization behavior of anhydrous milk fat (AMF), milk fat triacylglycerols (MF‐TAG), and MF‐TAG plus diacylglycerols (MF‐DAG). The crystallization process was monitored by measuring the solid fat content, turbidity, and scattering intensity of the crystallizing material, as well as by imaging using polarized light microscopy combined with digital image processing. In general, induction times followed the order MF‐DAG>AMF>MF‐TAG for all techniques. However, the absolute value for the induction times differed substantially; on average 3 min by microscopy, 7 min by light‐scattering spectroscopy, 13 min by turbidimetry, and 25 min by pulsed nuclear magnetic resonance. Microscopic imaging coupled to image processing proved to be the most sensitive method, suitable for the study of early events in the crystallization of fats.

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)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.004
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.030
GPT teacher head0.315
Teacher spread0.286 · 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 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

Citations70
Published2000
Admission routes1
Has abstractyes

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Same venueJournal of the American Oil Chemists SocietySame topicFood Chemistry and Fat AnalysisFrench-language works237,207