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Record W2169667874 · doi:10.1039/b715047d

Biodiesel: a green polymerization solvent

2008· article· en· W2169667874 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueGreen Chemistry · 2008
Typearticle
Languageen
FieldEngineering
TopicBiodiesel Production and Applications
Canadian institutionsUniversity of Ottawa
FundersUniversity of Ottawa
KeywordsPolymerizationSolventChain transferPolymer chemistryChemistrySolution polymerizationMethyl methacrylatePrecipitation polymerizationStyreneRadical polymerizationMethyl acrylateCatalytic chain transferAcrylateBulk polymerizationVinyl acetateChain-growth polymerizationMonomerOrganic chemistryPolymerCopolymer

Abstract

fetched live from OpenAlex

In an effort to use clean technologies, fatty acid methyl esters (FAME) produced from canola have been used as a polymerization solvent. Solution polymerizations of four commercially important monomers have been studied using FAME as a solvent. A series of methyl methacrylate (MMA), styrene (Sty), butyl acrylate (BA) and vinyl acetate (VAc) homopolymerizations in FAME were carried out at 60 °C at different solvent concentrations. Chain transfer to solvent rate constants were obtained using the Mayo method. The transfer constants increased in the order: MMA < Sty < BA < VAc. Under the conditions studied, the MMA solution polymerization in FAME was observed to behave as a precipitation polymerization. The estimated chain transfer to solvent rate constants were employed in a polymerization simulator to predict the polymerization rates and average molecular weights.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.127
Threshold uncertainty score0.459

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)0.0000.000

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 head0.016
GPT teacher head0.195
Teacher spread0.179 · 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