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Record W2073262618 · doi:10.1002/macp.201000743

A Novel Approach for Investigation of Chain Transfer Events by Pulsed Laser Polymerization

2011· article· en· W2073262618 on OpenAlexaff
A. N. Nikitin, Robin A. Hutchinson, Michael Buback, Pascal Hesse

Bibliographic record

VenueMacromolecular Chemistry and Physics · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Materials Analysis
Canadian institutionsQueen's University
Fundersnot available
KeywordsPolymerizationChain transferChemistryArrhenius equationChain (unit)Polymer chemistryRadical polymerizationAnalytical Chemistry (journal)Molar mass distributionChain terminationPhysical chemistryPolymerOrganic chemistryActivation energy

Abstract

fetched live from OpenAlex

Abstract Pulsed laser polymerization (PLP) with subsequent analysis of molecular mass distribution (MMD) is used to determine the rate coefficient of chain transfer to an agent A, ktrA, by varying pulse repetition rate such that the contributions of PLP‐induced and chain‐transfer‐induced peaks to the MMD change to a significant extent. It is shown by simulation that the relative heights of these peaks may be used to estimate ktrA. The method is applied to evaluation of the rate coefficient of chain transfer to dodecyl mercaptan with butyl methacrylate polymerizations at −11, 0, 20 and 40 °C. The Arrhenius parameters for this coefficient are determined to be: A(ktrA) = (2.2 ± 0.6) × 106 L · mol−1 · s−1 and Ea(ktrA) = (22.1 ± 0.7) kJ · mol−1. 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.

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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.029
GPT teacher head0.190
Teacher spread0.161 · 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

Citations10
Published2011
Admission routes1
Has abstractyes

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