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Approval of production waste application as modifiers of aluminum alloys

2021· article· en· W3171560940 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

VenueEngineering Journal of Satbayev University · 2021
Typearticle
Languageen
FieldEngineering
TopicBauxite Residue and Utilization
Canadian institutionsArcelorMittal (Canada)
Fundersnot available
KeywordsMaterials scienceAlloyRaw materialMetallurgyCorundumAluminiumMicrostructureSilica fumeIndustrial wasteRefining (metallurgy)MoldComposite materialWaste managementChemistry

Abstract

fetched live from OpenAlex

The results of a study of the effect of modifying additives from production waste of microsilica and corundum (Al2O3) powders on the structure and phase composition of the AD31 aluminum alloy are presented. In the conditions of the Karaganda Industrial University, melting of the AD31 aluminum alloy was carried out with the addition of 1% of waste powder of silicon production «Silicium Kazakhstan» (now «Tau-Ken Temir») (microsilica grade MK-85) and corundum powder (abrasive waste from cutting discs) as modifiers. The positive effect of modifying additives from industrial waste on the structure and properties of the alloy is revealed - the grain is refined, the phase composition changes, and the properties of modified aluminum alloys improve. To study the samples of the obtained modified alloys, the authors used the method of electron microscopy, as the simplest and fastest way to transfer information about the microstructure, elemental composition and distribution of elements in the sample volume. The conducted studies are relevant from the point of view of recycling waste from metallurgical industries, expanding the raw material base, as well as obtaining new materials with the required complex of functional 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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.556
Threshold uncertainty score0.377

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 head0.004
GPT teacher head0.159
Teacher spread0.155 · 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