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Record W4321240028 · doi:10.1080/19392699.2023.2179042

Coal rheology – the effect of coal origin, rank, and particle size

2023· article· en· W4321240028 on OpenAlexaffabout
Ted Todoschuk, Michelle Latosinski, Xianai Huang, Ka Wing Ng

Bibliographic record

VenueInternational Journal of Coal Preparation and Utilization · 2023
Typearticle
Languageen
FieldEngineering
TopicMineral Processing and Grinding
Canadian institutionsTeck (Canada)ArcelorMittal (Canada)
Fundersnot available
KeywordsCoalRheologyRank (graph theory)Particle sizeCoal rankParticle (ecology)Petroleum engineeringEnvironmental scienceMineralogyMining engineeringGeologyMaterials scienceMathematicsWaste managementComposite materialEngineeringPaleontology

Abstract

fetched live from OpenAlex

Coal rheology is a critical parameter for determining the coking and caking ability of metallurgical coals for cokemaking. The effect of rank, hardness differences due to rank, and particle size on the resultant fluidity and dilatation results were demonstrated for various rank Applachian coals in previous studies. Particles less than USA Standard screen size No. 140 had poorer rheology responses compared to other size fractions. For the third phase of this study, the effect of particle size and rank of Western Canadian coals were also evaluated. All samples and rheology parameters were determined prepared using the standard ASTM methods. In addition, rheology was also measured on sized subsets to determine the effect of particle size and rank on the overall rheology results but from a different geological era compared to Applachian coals. Particle size limits for the Gieseler and Dilatometer tests are suggested. The importance of using temperature range is also emphasized.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.315
Teacher spread0.295 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2023
Admission routes2
Has abstractyes

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