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A Statistical Analysis of Epoxy Polymer Reinforced with Micro Ceramic Particles

2016· article· en· W2554293342 on OpenAlex
Arthur Bernardes Lara Melo, Luí­s Fernando Lucas Paiva, Júlio César dos Santos, Túlio Hallak Panzera, Rodrigo Teixeira Santos Freire

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Research Updates in Polymer Science · 2016
Typearticle
Languageen
FieldEngineering
TopicTribology and Wear Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials scienceComposite materialPortland cementCeramicCuring (chemistry)EpoxyCompressive strengthPolymerCementMass fractionQuartzFactorial experiment

Abstract

fetched live from OpenAlex

A significant amount of research has been focused on the use of ceramic nano/micro particles to enhance the strength and stiffness of polymeric matrices. This work evaluates the effect of Portland cement or crystalline silica (quartz) particle inclusions into epoxy polymer. Two experiments were conducted based on a full factorial design analysis. Experiment I investigated the effect of Portland cement amount (ASTM III), two types of hardeners (HY 951 and 956) and two curing times (7 and 28 days) on the compressive behaviour and density of particulate composites. Experiment II evaluated the incorporation of quartz or cement particles by mixing different mass fraction levels, considering 28 days of curing time and HY 951 hardener. The samples were prepared in a randomized manufacturing process and tested in compression. The mechanical properties were significantly affected by the type of hardener used. Both particles can enhance the compressive strength and stiffness of the composites.

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)0.002
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 score0.076
Threshold uncertainty score0.560

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.018
GPT teacher head0.325
Teacher spread0.307 · 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