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Record W2047111394 · doi:10.1002/masy.201100001

Monte Carlo Simulation of the Microstructure of Linear Olefin Block Copolymers

2012· article· en· W2047111394 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 Symposia · 2012
Typearticle
Languageen
FieldMaterials Science
TopicPolymer crystallization and properties
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMonte Carlo methodCopolymerMicrostructureMaterials sciencePolymerOlefin fiberPolymerizationChain (unit)Reactivity (psychology)Block (permutation group theory)Polymer chemistryComposite materialMathematicsPhysicsGeometry

Abstract

fetched live from OpenAlex

Abstract Summary: Linear olefin block copolymers (OBCs) are novel polyolefins with unique properties developed using the chain shuttling polymerization technology. Typically, OBCs are made in a single reactor with two catalysts having different 1‐olefin reactivity ratios and a chain shuttling agent (CSA), producing linear polymer chains with complex, multi‐block structures, although a dual reactor approach is also possible In this study, OBC chain microstructures were examined using Monte Carlo simulation. Effects of polymerization parameters (chain shuttling probability, propagation probability, and catalyst ratio) on the distribution of number of blocks per chain were investigated and reported for the first time. These results provide useful insights on how to control and describe the microstructures of these important polymers and can be used to establish quantitative relationships between the microstructure and properties of OBCs.

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 score0.341

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 head0.009
GPT teacher head0.231
Teacher spread0.222 · 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