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MODIFICATION OF METAL BY NANOPOWDER INOCULATORS AT THE ROLLED SECTION STEEL CONTINUOUS CASTING MACHINE TO IMPROVE THE QUALITY OF ROLLED STEEL

2015· article· en· W2272553036 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

VenueIzvestiya Ferrous Metallurgy · 2015
Typearticle
Languageen
FieldEngineering
TopicEngineering and Environmental Studies
Canadian institutionsEVRAZ (Canada)
Fundersnot available
KeywordsMetallurgyContinuous castingSection (typography)Materials scienceCastingComputer science

Abstract

fetched live from OpenAlex

Investigation of the effect of metal modifying with nanopowder materials on the quality of rectangular continuously cast billets, structural shapes and reinforcing bar showed that the introduction of TiC х N y – Fe admixture in tundish ladle of continuous casting machine reduces segregation of elements in the ingot and pollution by non-metallic inclusions, increases its chemical and structural homogeneity. NPI application alters the structure of shapes and rebar; shape, size and topography of the location of non-metallic inclusions; as well as grain refining and improvement of the metalroll 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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.155
Threshold uncertainty score0.741

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.026
GPT teacher head0.245
Teacher spread0.220 · 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