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Margarine Processing Plants and Equipment

2020· other· en· W4211040790 on OpenAlexaff
Klaus A. Alexandersen, Saeed M. Ghazani, Alejandro G. Marangoni

Bibliographic record

VenueBailey's Industrial Oil and Fat Products · 2020
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicFood Chemistry and Fat Analysis
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsRaw materialFood scienceButterfatFood processingEngineeringBusinessPulp and paper industryMilk fatChemistry

Abstract

fetched live from OpenAlex

Abstract When designing margarine processing plants and choosing the equipment to be installed, a wide range of considerations have to be made with regard to issues like actual processing, hygiene, sanitation, and efficiency. In margarine production, oils and fats usually are considered to be the most important raw materials used, as oils and fats are significant in relation to the characteristics of the finished margarine. The type of oils or fats used has a considerable influence on the crystallization characteristics during the margarine processing, which has to be considered when choosing the equipment involved in the processing line. The criteria involved in choosing this equipment are to a certain extent based on the knowledge about product characteristics, polymorphism, and crystal structure of the margarine and related products. In this article, crystallization of oil and fat products, margarine processing equipment and packaging methods, processing methods, and specific process flows are discussed. Various oil types exhibiting interesting crystallization habits are reviewed along with certain specialized margarine or fat products and new processing methods such as interesterification and oleogelation. Storage of the finished products, as well as production quality control and hygiene, are also covered.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.775
Threshold uncertainty score0.865

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.041
GPT teacher head0.211
Teacher spread0.170 · 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 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

Citations1
Published2020
Admission routes1
Has abstractyes

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