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Record W1994633837 · doi:10.1002/app.25713

Memory functions in polymer modified asphalts

2007· article· en· W1994633837 on OpenAlexaff
Giovanni Polacco, Jiri Stastna, Peter Michalica, Matteo Cantù, Ludovit Zanzotto

Bibliographic record

VenueJournal of Applied Polymer Science · 2007
Typearticle
Languageen
FieldChemical Engineering
TopicRheology and Fluid Dynamics Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsStyreneViscoelasticityMaterials sciencePolymerCopolymerRelaxation (psychology)Polymer chemistryEthyleneModulusComposite materialPolymer scienceChemistryOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

Abstract The viscoelastic nonlinear behavior of several base and polymer modified asphalts (PMA) has been studied in step‐strain experiments. The polymers were poly(styrene‐ b ‐butadiene‐ b ‐styrene), poly(styrene‐ b ‐ethylene‐ co ‐butylene‐ b ‐styrene), poly(ethylene‐ r ‐vinylacetate) copolymers, and a linear low density poly(ethylene), which were chosen as representatives of the main categories of asphalt modifiers. Because of the complexity of the morphological structure of these materials, the relaxation modulus has only partial and qualitative similarities with that of melt or high concentrated solutions of entangled polymeric liquids. No time strain separability can be applied, and the relaxation experiments are conveniently described by means of the memory functions. These have been calculated both via a parametric fitting procedure and by interpolation algorithms. Results are presented, and a correlation between the PMA structure and the corresponding memory function is proposed for the investigated materials. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci 104: 2330–2340, 2007

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)0.001
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 score0.143
Threshold uncertainty score0.414

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.009
GPT teacher head0.238
Teacher spread0.229 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations13
Published2007
Admission routes1
Has abstractyes

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