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Record W4392382224 · doi:10.1016/j.tmater.2024.100026

Connectivity in binary mixtures of spherical particles

2024· article· en· W4392382224 on OpenAlexaff
Aurélien Sibellas, James Drummond, D. Mark Martinez, A.B. Phillion

Bibliographic record

VenueTomography of Materials and Structures · 2024
Typearticle
Languageen
FieldMaterials Science
TopicPickering emulsions and particle stabilization
Canadian institutionsMcMaster UniversityHamilton Health SciencesVancouver Biotech (Canada)University of British Columbia
Fundersnot available
KeywordsSPHERESBinary numberCoordination numberRange (aeronautics)VisualizationStatistical physicsMaterials scienceComputer scienceNanotechnologyMathematicsPhysicsArtificial intelligenceComposite material

Abstract

fetched live from OpenAlex

Mono- and poly-disperse assemblies of spherical particles are investigated in terms of their average and partial coordination numbers by means of X-ray microtomography using a novel morphology-based image processing method to statistically distinguish true contacting particles from very close ones having apparent contacts arising from image artefacts. This technique is shown to reduce overestimations given by the laborious liquid-bridge method while corroborating theoretical predictions such as Z ¯ ≤ 6 for random beds of mono-sized spheres and trends of the partial coordination numbers in binary mixtures of spheres. This method also provides a detailed and unbiased visualization of the long-range connectivity between similar particles which suggests that for partial coordination numbers Z ¯ i i > 3 , chains of particular contact-category are formed throughout the assembly.

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)0.000
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 score0.143
Threshold uncertainty score0.249

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 communication0.0000.000
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 head0.012
GPT teacher head0.254
Teacher spread0.242 · 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
Published2024
Admission routes1
Has abstractyes

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