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Record W2052469729 · doi:10.1002/macp.201400518

Mathematical Modeling of Crystallization Elution Fractionation of Ethylene/1‐Octene Copolymers

2014· article· en· W2052469729 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 Chemistry and Physics · 2014
Typearticle
Languageen
FieldMaterials Science
TopicCrystallization and Solubility Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsComonomerElutionFractionationCrystallizationCopolymerDissolutionEthyleneCrystallinityPolyolefinChemistryMaterials sciencePolymerChemical engineeringChromatographyPolymer chemistryOrganic chemistryCatalysisCrystallography

Abstract

fetched live from OpenAlex

Crystallization elution fractionation (CEF) is a relatively new polyolefin characterization technique used to estimate the chemical composition distribution (CCD) of semicrystalline copolymers. CEF is developed to enhance the resolution and reduce the analysis time of temperature rising elution fractionation (TREF) by separating polymer samples in both the crystallization and elution steps. A model based on the concept of population balance, crystallization/dissolution kinetics, and dispersion model is developed to understand the CEF fractionation mechanisms. The proposed CEF model is found to describe well the experimental CEF profiles of a series of ethylene/1‐octene copolymers with different comonomer contents. 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.

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: none
Teacher disagreement score0.528
Threshold uncertainty score0.338

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 head0.011
GPT teacher head0.236
Teacher spread0.226 · 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