MétaCan
Menu
Back to cohort

Hydrogenation: Processing Technologies

2020· other· en· W4242910836 on OpenAlex

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

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
KeywordsChemistryFood sciencePalm oilCatalysisOrganic chemistryPulp and paper industryEngineering

Abstract

fetched live from OpenAlex

Abstract Although there is a continued need for hydrogenation of oils and fats for food industry, in recent years the final hydrogenated products mainly switched to fully hydrogenated fats instead of partially hydrogenated oils. With the increasing consumer awareness about the deleterious effects of trans fatty acids, the consumption of industrially hydrogenated oils and fats has decreased. However, demand for substitution of hydrogenated fats with oils naturally high in saturated fatty acids, such as palm oil and its derivatives, is increasing. The current research on the elimination of trans ‐fatty acids in food products through innovations and developments in hydrogenation process, novel catalysts and supports, and using novel oils and fats sources could be promising solutions to eliminate or dramatically decrease trans fatty acids; however, these findings need to be practically confirmed in industrial scale production plants.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.752
Threshold uncertainty score0.593

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 integrity0.0010.000
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 head0.037
GPT teacher head0.208
Teacher spread0.171 · 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