MétaCan
Menu
Back to cohort
Record W4408448479 · doi:10.3103/s1068364x24601215

Kinetics of Reduction by Carbon from Special Coke Used in Electrothermal Silicon Production for the C–Fe–O System

2024· article· en· W4408448479 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

VenueCoke and Chemistry · 2024
Typearticle
Languageen
FieldEngineering
TopicIron and Steelmaking Processes
Canadian institutionsArcelorMittal (Canada)
Fundersnot available
KeywordsCokeKineticsSiliconReduction (mathematics)Carbon fibersProduction (economics)Materials scienceChemistryMetallurgyChemical engineeringEngineeringMathematicsComposite materialPhysics

Abstract

fetched live from OpenAlex

Kinetic features of the carbon in rexil special coke obtained from long-flame Shubarkol coal and used for electrothermal production of silicon are outlined. For the example of the C–Fe–O system, it is found that, in comparison with other reducing agents (graphite, blast furnace coke), rexil is characterized by high reaction rate and activation energy. Experimental and industrial tests regarding silicon production from ore in electric furnaces indicate that practically all of the charcoal in the batch may be replaced by rexil. For example, when the ratio of rexil and coal (in terms of fixed carbon C so ) is 80 : 20, the furnace productivity is increased, the degree of silicon extraction (91%) is increased, and the mean silicon content (97.8%) is increased.

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 score0.009
Threshold uncertainty score0.239

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 head0.005
GPT teacher head0.191
Teacher spread0.186 · 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