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Record W2121035389 · doi:10.1039/c4ra02810d

Practical and scalable preparation of 2-methyleneglutaronitrile via an efficient and highly selective head-to-tail dimerization of acrylonitrile catalysed by low-loading of tricyclohexylphosphine

2014· article· en· W2121035389 on OpenAlexaff
Lei Yu, Jun Wang, Xu Zhang, Hongen Cao, Genlin Wang, Kehong Ding, Qing Xu, Mark Lautens

Bibliographic record

VenueRSC Advances · 2014
Typearticle
Languageen
FieldChemistry
TopicAsymmetric Hydrogenation and Catalysis
Canadian institutionsUniversity of Toronto
FundersNational Natural Science Foundation of China
KeywordsTricyclohexylphosphineAcrylonitrileCatalysisChemistryHead (geology)SolventLigand (biochemistry)Combinatorial chemistryPolymer chemistryChemical engineeringOrganic chemistryCopolymerPolymer

Abstract

fetched live from OpenAlex

By carefully evaluating the effect of solvent, ligand, temperature, and time, the commercially available tricyclohexylphosphine was found to be a particularly effective catalyst for head-to-tail dimerization of acrylonitrile, providing an efficient, scalable, and highly selective method for preparation of the useful 2-methyleneglutaronitrile with a low catalyst loading.

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)0.001
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 score0.030
Threshold uncertainty score0.564

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.000
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 head0.007
GPT teacher head0.287
Teacher spread0.281 · 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 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

Citations15
Published2014
Admission routes1
Has abstractyes

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