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Record W2148351795 · doi:10.1002/cjce.5450810329

Effect of Dispersion on Particle Segregation Due to Sparged Air in a Hydrocyclone

2003· article· en· W2148351795 on OpenAlexafffundvenue
Shijie Liu, Zhengxiang Zhu, Jacob H. Masliyah

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2003
Typearticle
Languageen
FieldEngineering
TopicCyclone Separators and Fluid Dynamics
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHydrocycloneFractionationSlurryKraft processMaterials sciencePulp (tooth)Composite materialDispersion (optics)Kraft paperChromatographyMechanicsChemistryOptics

Abstract

fetched live from OpenAlex

Abstract Fractionation of kraft wood pulp fibres was carried out in a hydrocyclone. Long fibres tend to migrate to the low shear region and report to the overflow stream. Excellent fractionation was found at high pulp slurry feed rates with a split ratio between 0.07 and 0.3. However, when air bubbles are sparged, all the fibres are more uniformly distributed inside the hydrocyclone. When increasingly more bubbles are present, on the other hand, long fibres drain down slower because of rapidly rising air bubbles. Thus, more long fibres report to the overflow stream at extremely high air injection rates.

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 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.586
Threshold uncertainty score0.329

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 head0.003
GPT teacher head0.174
Teacher spread0.172 · 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 teacher head, 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

Citations0
Published2003
Admission routes3
Has abstractyes

Explore more

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