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Record W2026096218 · doi:10.3103/s0967091213060168

Modifying metal with nanopowder in a continuous bar-casting machine

2013· article· en· W2026096218 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

VenueSteel in Translation · 2013
Typearticle
Languageen
FieldEngineering
TopicAdvanced materials and composites
Canadian institutionsEVRAZ (Canada)
Fundersnot available
KeywordsIngotMaterials scienceRebarTundishMetallurgyBar (unit)Continuous castingLiquationGrain sizeCastingComposite materialMicrostructureAlloy

Abstract

fetched live from OpenAlex

The modification of metal by nanopowder is studied as a means of improving the quality of continuous-cast bar, complex components, and rebar. The introduction of TiC x N y -Fe nanopowder in the tundish of the continuous-casting machine reduces the liquation of the elements over the ingot cross section and the content of nonmetallic inclusions and also increases the structural and chemical uniformity. The use of nanopowder inoculators changes the structure of complex components (angle bar) and rebar, as well as the shape, size, and distribution of the nonmetallic inclusions, and also reduces the grain size and improves the mechanical properties.

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 score0.536
Threshold uncertainty score0.338

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 head0.011
GPT teacher head0.203
Teacher spread0.192 · 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