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Record W2080128253 · doi:10.1002/cjce.22051

CFD modelling of continuous protein extraction process using liquid‐solid circulating fluidized beds

2014· article· en· W2080128253 on OpenAlexaffvenue
Abbas Dadashi, Jesse Zhu, Chao Zhang

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2014
Typearticle
Languageen
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsWestern University
Fundersnot available
KeywordsComputational fluid dynamicsMass transferExtraction (chemistry)SCALE-UPProcess (computing)Fluidized bedChromatographyFluidized bed combustionMaterials scienceAdsorptionIon exchangeChemistryProcess engineeringMechanicsIonComputer scienceEngineeringPhysics

Abstract

fetched live from OpenAlex

Abstract A computational fluid dynamics (CFD) model was developed to describe the hydrodynamics and mass transfer in the process of continuous protein extraction from broth using a liquid‐solid circulating fluidized bed (LSCFB) ion exchange system. The CFD model took into account both the adsorption and desorption processes. The quantitative predictions for the protein concentration were compared favourably with the experimental data from a lab‐scale system. The model was used to investigate the effects of hydrodynamic and kinetic parameters on the performance of the LSCFB ion exchange system. It was demonstrated that the model is a robust tool to simulate, scale up, and optimize the LSCFB ion exchange systems for protein extraction process.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.107
Threshold uncertainty score0.694

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 head0.014
GPT teacher head0.208
Teacher spread0.194 · 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

Citations14
Published2014
Admission routes2
Has abstractyes

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