MétaCan
Menu
Back to cohort
Record W2170336883 · doi:10.5539/jmsr.v3n1p77

The Criterion of Particle-Induced Cracking of Filled Polymers

2013· article· en· W2170336883 on OpenAlexvenueno aff
С. Л. Баженов, G. P. Goncharuk

Bibliographic record

VenueJournal of Materials Science Research · 2013
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsNeckingMaterials scienceComposite materialBrittlenessPolypropylenePolymerPolyethyleneDiamondElongationParticle (ecology)CrackingToughnessUltimate tensile strength

Abstract

fetched live from OpenAlex

Failure of high density polyethylene, low density polyethylene, and polypropylene filled with grinded rubber particles was studied. In tension, particles debond from the matrix and initiate appearance of pores. Small particles lead to formation of elliptical pores. In contrast, large particles initiate appearance of diamond cracks leading to fast failure of filled polymer. In the intermediate case elliptical pore gradually transforms into diamond cracks. The diamond crack appears when the elongation of an elliptical pore reaches the critical crack tip opening of the unfilled polymer. The size D of filler particles should be lower than Dc = GIc/[(ld - 1)?d)], where GIc is the fracture toughness, sd - the draw stress and ld - the natural draw ratio of the matrix in the neck. Ductile or brittle behavior of filled polymer depends on whether the polymer yields uniformly or with necking. If the neck does not appear, filler particles usually do not initiate brittle fracture. In contrast, filled polymers, yielding with necking, often are brittle.

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)0.009
metaresearch head score (Gemma)0.001
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 score0.015
Threshold uncertainty score0.436

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.084
GPT teacher head0.390
Teacher spread0.305 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Materials Science ResearchSame topicAsphalt Pavement Performance EvaluationFrench-language works237,207