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Record W1965687560 · doi:10.1515/htmp-2012-0089

Hot Metal Desulphurization Using Waste Residues from the Aluminum Industry

2012· article· en· W1965687560 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueHigh Temperature Materials and Processes · 2012
Typearticle
Languageen
FieldEngineering
TopicBauxite Residue and Utilization
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBauxiteMaterials scienceRed mudRefining (metallurgy)MetalAluminiumOxideTitaniumMetallurgyTitanium dioxideChemical engineeringWaste management

Abstract

fetched live from OpenAlex

Abstract In this paper, the sources, properties and possible applications of waste residues from the aluminum industry as refining agents for the steel industry were investigated. Characterization of the potential fluxing agents was performed using a combination of XRD, XRF, DTA, and TGA. Experiments were carried out to examine the potential of hot metal desulphurization with fluxes made from these residue materials in comparison with those obtained from bauxite. To facilitate this comparative behavior of fluxes derived from different source materials, particular attention was given to the enhancing effects of controlled amounts of sodium oxide in contrast to the deleterious effects associated with the presence of silica and titanium dioxide on the desulphurization process. A major advantage of refining fluxes made from white mud waste products is that they contain significant amounts of sodium oxide and only very small concentrations of the oxides of silicon and titanium.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.429

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 head0.014
GPT teacher head0.218
Teacher spread0.204 · 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