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Record W2767276290 · doi:10.1080/03019233.2017.1394033

Viscous characteristics and modelling of CaO–Al <sub>2</sub> O <sub>3</sub> -based mould flux with B <sub>2</sub> O <sub>3</sub> as a substitute for CaF <sub>2</sub>

2017· article· en· W2767276290 on OpenAlexaff
Wei Yan, Weiqing Chen, Yindong Yang, Alexander McLean

Bibliographic record

VenueIronmaking & Steelmaking Processes Products and Applications · 2017
Typearticle
Languageen
FieldEngineering
TopicMetallurgical Processes and Thermodynamics
Canadian institutionsUniversity of Toronto
FundersCentral Research Institute, Fukuoka UniversityState Key Laboratory of Agrobiotechnology, China Agricultural UniversityChina Postdoctoral Science Foundation
KeywordsViscosityFlux (metallurgy)AluminiumActivation energyMaterials scienceThermodynamicsMineralogyMetallurgyChemistryComposite materialPhysical chemistryPhysics

Abstract

fetched live from OpenAlex

Following a series of laboratory studies on the development of fluoride-free or low-fluoride CaO–Al2O3-based mould flux for continuous casting of high-aluminium steel, the viscosity properties of CaO–Al2O3-based mould flux with B2O3 as a substitute for CaF2 were investigated using the rotating cylinder method. It was found that B2O3 behaved in a similar manner to CaF2 in changing the viscosity of the flux system. From calculations of the viscous activation energies, it was found that similar changes in the concentrations of CaF2 and B2O3 resulted in almost the same changes in activation energy. A viscosity prediction model was developed using the optical basicity concept as an indicator of melt behaviour. Predicted viscosity values showed good agreement with measurements reported in the literature.

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)0.000
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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

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 integrity0.0010.000
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 head0.019
GPT teacher head0.231
Teacher spread0.212 · 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

Citations26
Published2017
Admission routes1
Has abstractyes

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