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Record W2068020492 · doi:10.1209/0295-5075/104/56006

Topological correlations of grain faces in polycrystal with experimental verification

2013· article· en· W2068020492 on OpenAlexaff
Wenwen Li, Guoquan Liu, Hao Wang, Hao Zhang, Junhua Luan, Asad Ullah

Bibliographic record

VenueEurophysics Letters (EPL) · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced X-ray Imaging Techniques
Canadian institutionsUniversity of Alberta
FundersUniversity of California, Davis
KeywordsMonte Carlo methodTopology (electrical circuits)Face (sociological concept)Grain boundaryPhysicsStatistical physicsMaterials scienceCondensed matter physicsMathematicsMicrostructureCombinatoricsStatisticsMetallurgy

Abstract

fetched live from OpenAlex

How grain faces are arranged in three-dimensional grain structures is one of the outstanding problems in physics, biology and materials science. Based on the topological analysis of 477 real pure iron grains and 6093 Monte Carlo simulated grains, two forms of topological correlations are studied. The first correlation is Rivier's relation (Philos. Mag. B, 52 (1985) 795), in which the average number of edges of faces neighboring to e-edged faces on f-faceted grains is related to e and f; and the second correlation is the one derived in the current paper, in which a typical e-edged face in a polycrystal is a function of the average number of edges of its neighboring faces M(e). Both correlations are verified by experimental and simulation data.

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 score0.089
Threshold uncertainty score0.493

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 head0.007
GPT teacher head0.228
Teacher spread0.222 · 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

Citations4
Published2013
Admission routes1
Has abstractyes

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