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The Evolution of Ironmaking Process Based on Coal-Containing Iron Ore Agglomerates.

2001· article· en· W1985729459 on OpenAlexaff
W-K. Lu, D. Huang

Bibliographic record

VenueISIJ International · 2001
Typearticle
Languageen
FieldEngineering
TopicIron and Steelmaking Processes
Canadian institutionsMcMaster University
FundersIron and Steel Institute of Japan
KeywordsHearthAgglomerateMetallurgyCoalIron oreDirect reduced ironMaterials scienceIron oxideOpen hearth furnaceBlast furnacePelletsOxideWaste managementComposite materialEngineering

Abstract

fetched live from OpenAlex

Fundamentals of kinetics and mechanisms of iron oxide reduction of indurated pellets by reducing gases and of coal-containing iron ore composites, are reviewed. The gaseous products of the latter can be used to protect sponge iron from re-oxidation by a fully oxidized flame, provided the bed height of coal-containing iron ore agglomerates and the flame temperature are sufficiently high. Potential operational problems in RHF (Rotary Hearth Furnace) for tall beds and high flame temperature are discussed and a new hearth furnace, the Paired Straight Hearth (PSH) Furnace, is proposed.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.249
Teacher spread0.240 · 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 designTheoretical or conceptual
Domainnot available
GenreReview

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

Citations25
Published2001
Admission routes1
Has abstractyes

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