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Record W2003297407 · doi:10.3139/146.101554

Modeling short-range ordering in solutions

2007· article· en· W2003297407 on OpenAlexaff
Arthur D. Pelton, Youn‐Bae Kang

Bibliographic record

VenueInternational Journal of Materials Research (formerly Zeitschrift fuer Metallkunde) · 2007
Typearticle
Languageen
FieldEngineering
TopicMetallurgical Processes and Thermodynamics
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsTernary operationMaterials scienceBinary numberStatistical physicsRange (aeronautics)ThermodynamicsLattice (music)MiscibilityComputer sciencePhysicsMathematicsPolymer

Abstract

fetched live from OpenAlex

Abstract Various aspects of the modeling of short-range order in binary and ternary solutions using the Bragg – Williams (random mixing), associate, and quasichemical models are examined. The models are compared with respect to their ability to predict properties of ternary solutions from optimized binary model parameters in the presence of short-range order. It is shown how introducing short-range order through the quasichemical model can explain the observed flattened shape of most miscibility gaps. The combination of the quasichemical model for nearest-neighbor short-range order with the Bragg – Williams model for the remaining lattice interactions is described.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.078
GPT teacher head0.357
Teacher spread0.279 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations89
Published2007
Admission routes1
Has abstractyes

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