MétaCan
Menu
Back to cohort
Record W2891311405 · doi:10.1177/026248931803700201

Rotomolding of Foamed and Unfoamed GTR-LLDPE Blends: Mechanical, Morphological and Physical Properties

2018· article· en· W2891311405 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

VenueCellular Polymers · 2018
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Foaming and Composites
Canadian institutionsUniversité Laval
FundersNational Institutes of Health
KeywordsMaterials scienceLinear low-density polyethyleneComposite materialFlexural strengthUltimate tensile strengthBlowing agentIzod impact strength testBlow moldingHigh-density polyethyleneCompression moldingMolding (decorative)Flexural modulusComposite numberNatural rubberPolyethyleneMold

Abstract

fetched live from OpenAlex

In this work, a simple method is presented to produce ground tire rubber (GTR) -linear low density polyethylene (LLDPE) compounds and foams via rotational molding. In particular, different GTR concentrations (0 to 50% wt.) were dry-blended with different chemical blowing agent (CBA) content (0 to 1% wt.). From the samples produced, a complete set of characterization was performed in terms of mechanical properties (tensile, flexural and impact), density and morphological properties. The results show that increasing GTR content or CBA content not only decreased both tensile and flexural moduli, but decreased ultimate strength and strain at break. As expected, increasing blowing agent content decreased density. Besides, with respect to impact strength, the value of all samples decreased with the addition of GTR or CBA except for 0.2% wt. CBA of GTR-LLDPE composite foams, which nearly remain at the same level.

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 score0.003
Threshold uncertainty score0.596

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 head0.017
GPT teacher head0.224
Teacher spread0.207 · 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