MétaCan
Menu
Back to cohort
Record W2959749669 · doi:10.1016/j.dib.2019.104247

Data supporting micromechanical models for the estimation of Young's modulus and coefficient of thermal expansion of titanate nanotube/Y2W3O12/HDPE ternary composites

2019· article· en· W2959749669 on OpenAlexafffund
Patricia I. Pontón, Katia Yamada, Marco V. Guamán, Michel B. Johnson, Mary Anne White, Bojan A. Marinković

Bibliographic record

VenueData in Brief · 2019
Typearticle
Languageen
FieldMaterials Science
TopicThermal Expansion and Ionic Conductivity
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaEscuela Politécnica NacionalConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsHigh-density polyethyleneThermal expansionMaterials scienceComposite materialTernary operationTitanateNanotubeComposite numberThermalModulusWork (physics)PolyethyleneThermodynamicsCeramicComputer scienceCarbon nanotubePhysics

Abstract

fetched live from OpenAlex

This article presents several micromechanical models to predict the Young's modulus and the coefficient of thermal expansion of titanate nanotube/Y2W3O12/HDPE composites. The equations and assumptions of the selected micromechanical models are described in detail for this ternary system. Data of the elastic constants, coefficient of thermal expansion of composite components and other associated parameters, obtained either by literature survey or processing of literature information, are compiled in this work. For further interpretation of the data presented in this article, please see our research article entitled “The effect of titanate nanotube/Y2W3O12 hybrid fillers on mechanical and thermal properties of HDPE-based composites” (Pontón et al., 2019).

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.721
Threshold uncertainty score0.273

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.048
GPT teacher head0.303
Teacher spread0.255 · 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

Citations3
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueData in BriefSame topicThermal Expansion and Ionic ConductivityFrench-language works237,207