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Record W4280635287 · doi:10.3390/met12050862

Continuous Casting Practices for Steel: Past, Present and Future

2022· article· en· W4280635287 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.

Bibliographic record

VenueMetals · 2022
Typearticle
Languageen
FieldEngineering
TopicMetallurgical Processes and Thermodynamics
Canadian institutionsMcGill University
Fundersnot available
KeywordsCasterContinuous castingCastingManufacturing engineeringEngineeringQuality (philosophy)DrumMetallurgyMechanical engineeringMaterials science

Abstract

fetched live from OpenAlex

This historical review of casting methods used to produce sheets of steel for automobiles, household products, rocket bodies, etc., all point toward the development of one-step commercial processes, which are capable of casting liquid steel directly into a final sheet product. Progress towards this goal is confirmed by successful advances being made, but there remain major difficulties in reaching it. We concur that the conventional continuous casting method remains the current process of choice for highest-quality steel sheet products, but the ESP TSC (Endless Strip Production—Thin Slab Caster) approach is now highly competitive. Similarly, the original goal of Sir Henry Bessemer to produce a direct strip-making twin-drum caster, in 1856, finally came to lasting commercial fruition at CASTRIP/NUCOR. Nonetheless, a newer approach, promoted by Salzgitter, termed DSP (Direct Strip Production), or promoted by MMPC/MetSim as HSBC (Horizontal Single Belt Casting), has several advantages over CASTRIP in terms of microstructures and productivity. As such, the pros and cons of current methods are reviewed within this brief history of casting.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.679
Threshold uncertainty score0.331

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 head0.021
GPT teacher head0.255
Teacher spread0.234 · 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