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Record W2301170305 · doi:10.1002/mren.201500075

Analysis of Ethylene/1-Olefin Copolymers Made with Ziegler-Natta Catalysts by Deconvolution of Molecular Weight and Average Short Chain Branching Distributions

2016· article· en· W2301170305 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

VenueMacromolecular Reaction Engineering · 2016
Typearticle
Languageen
FieldChemistry
TopicOrganometallic Complex Synthesis and Catalysis
Canadian institutionsUniversity of Alberta
FundersChina Scholarship CouncilNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsComonomerBranching (polymer chemistry)CopolymerPolymer chemistryGel permeation chromatographyPolymerizationEthyleneMolar mass distributionPolymerOlefin fiberMaterials scienceNattaPolyethyleneCatalysisChemistryOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

In this article a systematic method is proposed to deconvolute the time-dependent molecular weight distributions (MWD) and average comonomer fraction profiles of ethylene/1-olefin copolymers made with heterogeneous Ziegler–Natta catalysts. These distributions with a high-temperature gel permeation chromatography equipped with an infrared detector at four different polymerization times have been measured and used this information to infer how the fractions of polymer made on each site type varied with polymerization time. The model estimates here the minimum number of active site types needed to describe these copolymers, the MWD of polymer populations made on each site type, and their average comonomer fractions. This method is useful to quantify the microstructure of olefin copolymers made with multiple site type catalysts using the least number of adjustable parameters.

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 score0.152
Threshold uncertainty score0.856

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.183
Teacher spread0.180 · 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