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Record W2064158441 · doi:10.1002/adv.10049

Binary blends of EVA and metallocene‐catalyzed ethylene‐α‐olefin copolymers and their film properties

2003· article· en· W2064158441 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

VenueAdvances in Polymer Technology · 2003
Typearticle
Languageen
FieldMaterials Science
TopicPolymer crystallization and properties
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaGovernment of Ontario
KeywordsMaterials scienceCopolymerDie swellEthyleneElastomerMetallocenePost-metallocene catalystOlefin fiberComposite materialPolymer chemistryUltimate tensile strengthExtrusionCatalysisPolymerizationPolymerOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Blends of Ethylene‐Vinyl Acetate (EVA) copolymer with a metallocene (single‐site type) catalyzed elastomeric ethylene‐α‐olefin copolymer have been investigated, with a focus on film applications. These blends were found to be immiscible in the melt and solid state, but mechanically compatible. EVA rich blends had a coarser morphology and showed more pronounced shear thinning and elastic behavior, suggesting better processability during the extrusion film blowing process. Ethylene‐α‐olefin copolymer rich blends displayed finer morphologies, better tensile, heat seal, and optical properties and less extrudate swell. © 2003 Wiley Periodicals, Inc. Adv Polym Techn 22: 209–217, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/adv.10049

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 score0.290
Threshold uncertainty score0.746

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 studies0.0000.001
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 head0.010
GPT teacher head0.227
Teacher spread0.217 · 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