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Record W2744558272 · doi:10.1039/c7sm00985b

Crack opening: from colloidal systems to paintings

2017· article· en· W2744558272 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.

fundA Canadian funder is recorded on the work.
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

VenueSoft Matter · 2017
Typearticle
Languageen
FieldEngineering
TopicEpoxy Resin Curing Processes
Canadian institutionsnot available
FundersAgence Nationale de la RechercheUniversity of Windsor
KeywordsColloidPaintingMaterials scienceChemistryNanotechnologyChemical engineeringPolymer scienceArtVisual artsEngineeringOrganic chemistry

Abstract

fetched live from OpenAlex

Shrinkage cracks are observed in many materials, particularly in paintings where great interest lies in deducing quantitative information on the material with the aim of proposing authentication methods. We present experimental measurements on the crack opening induced by the drying of colloidal layers and compare these results to the case of a pictorial layer. We propose a simple model to predict the crack width as a function of the thickness of the drying layer, based on the balance between the drying stress buildup and the shear frictional stress with the substrate. Key parameters of the model include the mechanical properties that are measured experimentally using micro-indentation testing. A good agreement between theory and experimental data for both colloidal layers and the real painting is found. These results, by comparing the shrinkage cracks in model layers and in pictorial layers, validate the method based on the use of colloidal systems to simulate and to reproduce drying cracks in paintings.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.997

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 studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.004

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 head0.014
GPT teacher head0.238
Teacher spread0.225 · 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