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Record W2013971420 · doi:10.1002/mren.200900086

Reducing ATRP Catalyst Concentration in Batch, Semibatch and Continuous Reactors

2010· article· en· W2013971420 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.

Bibliographic record

VenueMacromolecular Reaction Engineering · 2010
Typearticle
Languageen
FieldChemistry
TopicAdvanced Polymer Synthesis and Characterization
Canadian institutionsQueen's University
Fundersnot available
KeywordsDispersityCatalysisMonomerCopperPolymerCopolymerChemical engineeringAcrylatePolymer chemistryMethacrylateMaterials scienceSolubilityBatch reactorChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract An overview of solution ATRPs carried out in batch, semibatch and continuous tubular and stirred‐tank reactor systems is presented. Initial work using a heterogeneous catalyst system with copper to polymer chain ratios of close to unity demonstrated the versatility of ATRP in producing homopolymer and copolymer at reasonable rates with good MW control and narrow polydispersity. The significant drawbacks of low catalyst solubility and high copper levels are now being addressed through use of the ARGET ATRP chemistry. Nearly colorless acrylate and methacrylate polymers have been produced with copper catalyst levels below 50 ppm (relative to monomer), with excellent control of MW obtained both in batch and continuous systems. magnified 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.

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 score0.009
Threshold uncertainty score0.742

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 head0.003
GPT teacher head0.187
Teacher spread0.185 · 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