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Record W2899590644 · doi:10.1088/1361-651x/aaef22

Ordering of carbon in highly supersaturated <i>α</i> -Fe

2018· article· en· W2899590644 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueModelling and Simulation in Materials Science and Engineering · 2018
Typearticle
Languageen
FieldEngineering
TopicAdvanced Materials Characterization Techniques
Canadian institutionsUniversity of British Columbia
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsMonte Carlo methodMaterials scienceMean field theoryCarbon fibersCarbideThermodynamicsStatistical physicsCondensed matter physicsPhysicsStatisticsMathematics

Abstract

fetched live from OpenAlex

Abstract Metropolis Monte Carlo is used to investigate the Zener ordering as the carbon content of body centered cubic iron is increased. Thanks to a fast simulation algorithm, the equilibrium state for a wide range of temperature and carbon content are investigated. These results are compared to a thermodynamical mean-field model that accounts for long range elastic interaction and configurational entropy. At carbon levels of above 2 at.%, it is found that the mean-field model overestimates the order–disorder transition temperature. This is due to local repulsive C–C interactions not accounted for in the mean-field model. Forbidding some strongly repulsive configurations leads to a better agreement between the mean-field model and Metropolis Monte Carlo simulations. At high concentration carbon atoms in solid solution exhibits local configurations typical of the Fe 16 C 2 carbide.

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 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 score0.119
Threshold uncertainty score0.431

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 head0.223
Teacher spread0.211 · 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