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Record W2921942728 · doi:10.3390/met9030309

Model Development for Refining Rates in Oxygen Steelmaking: Impact and Slag-Metal Bulk Zones

2019· article· en· W2921942728 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMetals · 2019
Typearticle
Languageen
FieldEngineering
TopicMetallurgical Processes and Thermodynamics
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRefining (metallurgy)SteelmakingSlag (welding)Basic oxygen steelmakingMetallurgyImpurityMaterials scienceEnvironmental scienceOxygenJet (fluid)ChemistryMechanics

Abstract

fetched live from OpenAlex

A new approach has been adopted to predict the contribution of the impact and slag-metal bulk zones to the refining rates of impurities in a top blown oxygen steelmaking process. The knowledge pertaining to the behavior of top-jets and bottom stirring plumes (water model and industrial studies) was adapted. For the impact zone, the surface renewal generated by the top jet as well as bottom stirring plumes is incorporated in the current model, whereas in the case of slag-metal bulk zones the surface renewal is caused solely by the bottom stirring plumes. This approach helped in achieving a more explicit use of process parameters in quantifying the slag formation. The results suggest a minor contribution of these two zones to the overall refining of impurities throughout the oxygen blow.

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 score0.041
Threshold uncertainty score0.573

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 head0.028
GPT teacher head0.270
Teacher spread0.242 · 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