MétaCan
Menu
Back to cohort
Record W2040008406 · doi:10.3139/146.101267

Re-optimization of the Mg–Sb system under topological constraints

2006· article· en· W2040008406 on OpenAlexaff
Dmitri V. Malakhov, Thevika Balakumar

Bibliographic record

VenueInternational Journal of Materials Research (formerly Zeitschrift fuer Metallkunde) · 2006
Typearticle
Languageen
FieldEngineering
TopicThermodynamic and Structural Properties of Metals and Alloys
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPhase diagramMaterials sciencePhase (matter)Optimization problemSpinodal decompositionTopology (electrical circuits)MiscibilitySyntaxMathematical optimizationThermodynamicsComputer scienceAlgorithmMathematicsPhysicsComposite materialCombinatoricsArtificial intelligencePolymerQuantum mechanics

Abstract

fetched live from OpenAlex

Abstract Non-existing inverted miscibility gaps in the liquid phase at high temperatures, reappearance of the liquid phase at low temperatures or reappearance of a solid phase at elevated temperatures, and other “approximation phantoms” sometimes result from thermodynamic assessments. A method for struggling against such artifacts is proposed. The method is based on introducing a sufficiently dense mesh of knots (not related to experimental points utilized in the optimization) and ensuring that specific inequality conditions (topological constraints) governing the appearance of the phase diagram are satisfied in these knots. It is shown that the syntax of the language describing conditions and experiments in the PARROT module of Thermo-Calc is suitable for performing such optimization. The workability of the approach proposed is exemplified by carrying out a re-optimization of the Mg–Sb system.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0040.000

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 head0.027
GPT teacher head0.279
Teacher spread0.252 · 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 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

Citations9
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Materials Research (formerly Zeitschrift fuer Metallkunde)Same topicThermodynamic and Structural Properties of Metals and AlloysFrench-language works237,207