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Record W2613924537 · doi:10.1002/marc.201700105

Propagation Kinetics of Isoprene–Glycidyl Methacrylate Copolymerizations Investigated via PLP–SEC

2017· article· en· W2613924537 on OpenAlexaff
Florian Brandl, Marco Drache, Jan E. S. Schier, Tristan Nentwig, David Contreras López, Enrique Saldívar‐Guerra, Robin A. Hutchinson, Sabine Beuermann

Bibliographic record

VenueMacromolecular Rapid Communications · 2017
Typearticle
Languageen
FieldChemistry
TopicAdvanced Polymer Synthesis and Characterization
Canadian institutionsQueen's University
Fundersnot available
KeywordsIsopreneGlycidyl methacrylateKineticsCopolymerPolymerizationPolymer chemistryMaterials sciencePolymerMethacrylateRadical polymerizationSize-exclusion chromatographyChemistryComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

Pulsed-laser polymerization combined with polymer analysis by NMR and size-exclusion chromatography is used to study the radical copolymerization kinetics of isoprene (IP) with glycidyl methacrylate (GMA). The copolymer is characterized by a close-to-alternating microstructure, with the addition of IP leading to a significant decrease in the composition-averaged propagation rate coefficient. A rigorous fitting strategy is developed to fit a mixed penultimate model to the data, with the selectivity of the IP, but not the GMA, macroradical dependent on the penultimate unit.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.608
Threshold uncertainty score1.000

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.025
GPT teacher head0.275
Teacher spread0.251 · 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.

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

Citations11
Published2017
Admission routes1
Has abstractyes

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