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Record W2083566774 · doi:10.1002/app.33785

Influence of chain microstructure on ethylene–norbornene copolymer film properties

2011· article· en· W2083566774 on OpenAlexaff
Shaojie Liu, Zhen Yao, Lin Chen, Binbin Dai, Kun Cao, Bo‐Geng Li, Shiping Zhu

Bibliographic record

VenueJournal of Applied Polymer Science · 2011
Typearticle
Languageen
FieldChemistry
TopicOrganometallic Complex Synthesis and Catalysis
Canadian institutionsMcMaster University
Fundersnot available
KeywordsCopolymerNorborneneRefractive indexMaterials sciencePolymer chemistryEthyleneChemical engineeringPolarMicrostructurePolymerOrganic chemistryChemistryComposite material

Abstract

fetched live from OpenAlex

Abstract The effects of copolymer composition, copolymer composition distribution, and polar α‐olefin incorporation on transparency, refractive index, and hydrophilicity of resultant ethylene–norbornene copolymer films were investigated. It has been found that the transparency is mainly determined by the copolymer composition distribution. The samples having uniform compositions gave better transparency. However, the copolymer composition distribution had little effect on refractive index. The refractive index increased linearly with increasing norbornene content. Furthermore, the incorporation of polar α‐olefin with long carbon chain improved refractive index and hydrophilicity of the films. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2011

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 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 categoriesInsufficient payload (model declined to judge)
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 score0.022
Threshold uncertainty score0.998

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.203
Teacher spread0.187 · 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 teacher head, not a consensus.

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

Citations7
Published2011
Admission routes1
Has abstractyes

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