MétaCan
Menu
Back to cohort

Fluid Slag Skimming from Steel Ladles.

2001· article· en· W2063847621 on OpenAlexaff
K. W. Ng, R. Harris

Bibliographic record

VenueISIJ International · 2001
Typearticle
Languageen
FieldEngineering
TopicMetallurgical Processes and Thermodynamics
Canadian institutionsMcGill University
Fundersnot available
KeywordsLadleSteelmakingSlag (welding)MetallurgyWater modelMaterials scienceReynolds numberLiquid steelMechanicsChemistryTurbulence

Abstract

fetched live from OpenAlex

A 1/7 scale model was constructed to physically simulate the skimming process of desulphurization slag from the transfer ladle used in the steelmaking industry. 1-decanol and water were used to represent the slag and the underlying molten steel, respectively. It was observed that the underlying liquid surface circulation created by three impinging gas jets in glancing contact with the bath surface would carry the slag towards the skimming mouth. The Reynolds number of the jets (I.D. 0.01 m) inclined 50° to the horizontal was 6100. In the same amount of time, 70% of the slag originally charged to the tank was skimmed with the assistance of the jets in comparison to 20 % when no jets were used. This approach to slag flow control was considered much more effective and less generally damaging than the use of submerged gas injection.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.209
Teacher spread0.200 · 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

Citations3
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueISIJ InternationalSame topicMetallurgical Processes and ThermodynamicsFrench-language works237,207