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Record W2052210584 · doi:10.1002/cjce.5450820302

Size Segregation of Nickel Pellets Flowing into a Packed Bed

2004· article· en· W2052210584 on OpenAlexafffundvenue
Paul A. Moysey, N. V. Rama Rao, M. H. I. Baird

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2004
Typearticle
Languageen
FieldEngineering
TopicIron and Steelmaking Processes
Canadian institutionsMcMaster University
FundersMcMaster University
KeywordsPelletsPelletMaterials scienceNickelPacked bedComposite materialMechanicsGeometryMetallurgyChromatographyChemistryMathematicsPhysics

Abstract

fetched live from OpenAlex

Abstract The size segregation of nickel pellets fed to a packed bed has been measured with mixtures of sizes ranging from less than 1 mm to about 10 mm. The pellet mixture is fed to one side of a rectangular cell and then samples are removed from different lateral positions in the cell for screen analysis. During the feeding process the finer pellets tend to percolate vertically downwards while the larger pellets tend to roll down the sloping surface of the bed. The resulting segregation has been correlated with the size distribution of the feed pellets and the lateral position in the cell, using polynomial equations with three or four adjustable coefficients.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.178
Teacher spread0.173 · 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 designBench or experimental
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
Published2004
Admission routes3
Has abstractyes

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