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Record W4252183787 · doi:10.1002/cjce.23017

Issue Highlights

2017· article· en· W4252183787 on OpenAlexvenueaboutno aff

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2017
Typearticle
Languageen
FieldChemistry
TopicSynthetic Organic Chemistry Methods
Canadian institutionsnot available
Fundersnot available
KeywordsMetathesisHomogeneousCatalysisChemistryContext (archaeology)Salt metathesis reactionOrganic chemistryHomogeneous catalysisCitationHeterogeneous catalysisComputer scienceWorld Wide WebMathematicsGeographyCombinatorics

Abstract

fetched live from OpenAlex

Catalytic olefi n metathesis is one of the most emerging tools in synthetic chemistry that can be used explicitly to produce high value products from unsaturated fats and oil feedstock.This review article focuses on the efforts directed toward the development of heterogeneous olefi n metathesis catalytic systems with emphasis on their activity, stability, and reusability in the context of olefi n metathesis of natural fats/oils derivatives.Heterogenization/immobilization of active homogeneous catalysts aspect is discussed.Furthermore, the following topics are addressed: (i) Homogeneous versus heterogeneous catalysis; (ii) Metal-alkylidene based heterogeneous catalyst systems; and (iii) Alkylidene-free heterogeneous catalyst systems.[1]

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)0.003
metaresearch head score (Gemma)0.012
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.289
Threshold uncertainty score0.967

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0070.003
Open science0.0020.002
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.2890.136

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 head0.012
GPT teacher head0.233
Teacher spread0.221 · 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
GenreEditorial

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

Citations0
Published2017
Admission routes2
Has abstractyes

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