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Record W1856333624 · doi:10.1139/cjp-2014-0667

Multiple slips effects on MHD Casson fluid flow in porous media with radiation and chemical reaction

2015· article· en· W1856333624 on OpenAlexaffvenue
Fazle Mabood, Waqar A. Khan, A. I. Md. Ismail

Bibliographic record

VenueCanadian Journal of Physics · 2015
Typearticle
Languageen
FieldEngineering
TopicNanofluid Flow and Heat Transfer
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMagnetohydrodynamic driveMagnetohydrodynamicsMass transferPhysicsThermal radiationPorous mediumMechanicsHomotopy analysis methodDimensionless quantityHeat transferThermodynamicsBoundary layerFluid dynamicsFlow velocityFlow (mathematics)PorosityMagnetic fieldMaterials scienceComposite materialNonlinear system

Abstract

fetched live from OpenAlex

An investigation is carried out on magnetohydrodynamic (MHD) boundary layer flow as well as heat and mass transfer of a Casson fluid in a porous medium under the action of multiple slips, thermal radiation, and chemical reaction. An analytical solution has been obtained for the velocity, temperature, and concentration of the Casson fluid via the homotopy analysis method (HAM). Graphical and numerical demonstrations of the convergence of the HAM solutions are provided. The effect of certain parameters on the dimensionless velocity, temperature, concentration, as well as on the skin friction coefficient and heat and mass transfer rates are illustrated and examined in detail. A comparison with previously published data has been carried out and good agreement was found.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.010
GPT teacher head0.181
Teacher spread0.170 · 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 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

Citations26
Published2015
Admission routes2
Has abstractyes

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