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Record W2154430071 · doi:10.1002/app.12824

High density polyethylene foams. IV. Flexural and tensile moduli of structural foams

2003· article· en· W2154430071 on OpenAlexaff
Yaolin Zhang, Denis Rodrigue, A. Aı̈t-Kadi

Bibliographic record

VenueJournal of Applied Polymer Science · 2003
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Foaming and Composites
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMaterials scienceFlexural strengthComposite materialUltimate tensile strengthFlexural modulusYoung's modulusCompression moldingPolyethylene

Abstract

fetched live from OpenAlex

Abstract High density closed‐cell polyethylene foams (450–950 kg/m3) were prepared by compression molding, and their flexural and tensile moduli were measured in order to study (1) the normalized modulus as a function of the normalized density, and (2) the effect of thin skins on flexural and tensile moduli. For the flexural data, it was found that the model of Gonzalez and the I‐beam model of Hobbs predicted the data very well in the range of void volume fractions under study (0–55%). For the tensile data, it was found that a combination of the differential scheme or the square power‐law model with the sandwich structure gave the best predictions. Finally, we found that thin skins have an important effect on the flexural properties of polymer foams, while they seem to have a negligible effect on the tensile properties. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 90: 2139–2149, 2003

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.219
Teacher spread0.213 · 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 source (direct Gemma or distilled Codex), 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

Citations37
Published2003
Admission routes1
Has abstractyes

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