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Record W4313245010 · doi:10.3390/met13010062

Effect of Return Fines Embedding on the Sintering Behaviour of Vanadium Titanium Magnetite Concentrates

2022· article· en· W4313245010 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
TopicIron and Steelmaking Processes
Canadian institutionsMcMaster University
Fundersnot available
KeywordsSinteringMaterials scienceTitaniumMetallurgyMagnetiteVanadiumComposite materialYield (engineering)

Abstract

fetched live from OpenAlex

To improve the permeability of sinter packed bed for achieving the efficient utilization of low-grade iron bearing minerals, the effect of the returned fines embedding on productivity, yield, flame front speed (FFS) in the vanadium titanium magnetite (VTM) sintering process, tumble index (TI) of sinter, and permeability of the sinter packed bed was clarified. Results indicate that the productivity, yield, flame front speed, and tumble index of the vanadium titanium magnetite sintering process are all increased to a certain extent after embedding different sizes of returned fines, and the optimal sintering indices occur when the particle size of return fines for embedding is 3~5 mm. The optimal mass ratio of return fines for embedding was confirmed at 80%, and a continued increase in the mass ratio results in a decrease in flame front speed, yield, productivity, and tumble strength. Among the five different possible locations of embedded return fine layer, the middle-lower layer corresponds to the highest flame front speed. As the mass ratio of return fines for embedding is enhanced from 0% to 50%, the permeability of the sinter packed bed is improved at each stage of sintering.

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 score0.193
Threshold uncertainty score0.502

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 head0.009
GPT teacher head0.237
Teacher spread0.228 · 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