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Record W2614492709 · doi:10.1002/macp.201700107

Practical Chain‐End Reduction of Polymers Obtained with ATRP

2017· article· en· W2614492709 on OpenAlexaff
Will R. Gutekunst, Athina Anastasaki, David J. Lunn, Nghia P. Truong, Richard Whitfield, Glen R. Jones, Nicolas J. Treat, Allison Abdilla, Bryan E. Barton, Paul G. Clark, David M. Haddleton, Thomas P. Davis, Craig J. Hawker

Bibliographic record

VenueMacromolecular Chemistry and Physics · 2017
Typearticle
Languageen
FieldChemistry
TopicAdvanced Polymer Synthesis and Characterization
Canadian institutionsDow Chemical (Canada)
FundersCalifornia NanoSystems InstituteDivision of Materials ResearchMaterials Research Science and Engineering Center, Harvard UniversityUniversity of California, Santa BarbaraDow Materials Institute, Dow Chemical CompanyEuropean CommissionNational Institutes of HealthNational Science FoundationLubrizolDow Chemical Company
KeywordsPolymerBromineHalogenationPolymer chemistryChemistryMonomerHalogenChlorineCatalysisOrganic chemistryAlkyl

Abstract

fetched live from OpenAlex

A practical and user‐friendly strategy for the chain‐end reduction of halogen terminated polymers that employs hydrogen gas and heterogeneous catalysis (palladium on carbon) is reported. Quantitative dehalogenation of a wide variety of monomer families (polystyrenes, polyacrylates, and polymethacrylates) with either chlorine or bromine chain‐ends is observed. The utility of this chain‐end reduction is further highlighted by mild reaction conditions, simple purification, and compatibility with a wide range of solvents. image

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.010
GPT teacher head0.250
Teacher spread0.240 · 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 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

Citations16
Published2017
Admission routes1
Has abstractyes

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