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Record W2045142101 · doi:10.1002/cjce.5450810316

A Method for the Detection of Defluidized Zones in Slurry Bubble Columns

2003· article· en· W2045142101 on OpenAlexaffvenue
Ahad Emami, Cédric Briens

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2003
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsWestern University
Fundersnot available
KeywordsSpargingSlurryBubbleThermistorCeramicChemistryHeat transferAnalytical Chemistry (journal)Materials scienceChromatographyMineralogyThermodynamicsMechanicsComposite materialPhysics

Abstract

fetched live from OpenAlex

Abstract The formation of defluidized zones was studied in a laboratory slurry bubble column equipped with heat transfer probes. The probes were small thermistors 2.4 mm in diameter. Dionized water and air were used as a liquid and gas phase, respectively. Solids were fine ceramic particles with mean size of 19.2 μm and density of 2244 kg/m 3 . The effects of solids holdup (up to 30 wt% on gas free basis), gas superficial velocity (0.01‐0.09 m/s), sparger height (0.01‐0.09 m) on defluidized zones formation was studied. Cycle analysis of the local heat transfer fluctuations reliably detected the local formation of defluidized zones for each condition.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.510
Threshold uncertainty score0.254

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.006
GPT teacher head0.193
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

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 designSimulation or modeling
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

Citations6
Published2003
Admission routes2
Has abstractyes

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