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Record W3084142316 · doi:10.5650/jos.ess20055

Catalytic Transfer Hydrogenation of Low-erucic-acid Rapeseed Oil over a Ni-Ag<sub>0.15</sub>/SBA15 Catalyst

2020· article· en· W3084142316 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

VenueJournal of Oleo Science · 2020
Typearticle
Languageen
FieldEngineering
TopicCatalysis and Hydrodesulfurization Studies
Canadian institutionsScience North
Fundersnot available
KeywordsErucic acidRapeseedAmmonium formateChemistryCatalysisOleic acidIodine valueSodium formateOrganic chemistryLinoleic acidNuclear chemistryFood scienceFatty acidBiochemistryFormic acid

Abstract

fetched live from OpenAlex

The kinetics of catalytic transfer hydrogenation (CTH) of low-erucic-acid rapeseed oil using ammonium formate as a hydrogen donor over a Ni-Ag0.15/SBA15 catalyst were studied. Then, a kinetic model for the hydrogenation of low-erucic-acid rapeseed oil was established, and it was found that the reaction rate constants of hydrogenations of 9c-18:1 and 12c-18:1 oleic acid were 0.1262 and 0.0148, and the catalytic selectivity of linoleic acid was 2.04. For the catalyst loading of 0.23%, the hydrogenation temperature was 80°C, the ammonium formate concentration was 0.32 mol/50 mL, and the low-erucic-acid rapeseed oil was hydrogenated in 90 min; it was also found that the iodine value of low-erucic-acid rapeseed oil was 80 g I2/100 g, the oleic acid content was 65%, and the trans fatty acids (TFAs) content was only 6.7%. Therefore, CTH may be widely used in the modification of oils and 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.

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 score0.023
Threshold uncertainty score0.956

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.011
GPT teacher head0.212
Teacher spread0.202 · 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