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Record W4214760321 · doi:10.1002/num.22874

<scp>Cattaneo–Christov</scp> heat flux model for three‐dimensional magnetohydrodynamic flow of an Eyring Powell fluid over an exponentially stretching surface with convective boundary condition

2022· article· en· W4214760321 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNumerical Methods for Partial Differential Equations · 2022
Typearticle
Languageen
FieldEngineering
TopicNanofluid Flow and Heat Transfer
Canadian institutionsFanshawe College
Fundersnot available
KeywordsMagnetohydrodynamic driveMechanicsHeat fluxConvectionHeat transferCompressibilityNanofluidConvective heat transferThermodynamicsParasitic dragHeat transfer coefficientFlow (mathematics)MagnetohydrodynamicsBoundary layerMagnetic fieldPhysics

Abstract

fetched live from OpenAlex

Abstract The present model concentrates on three‐dimensional steady incompressible flow of an Eyring‐Powell nanofluid past an exponentially stretching sheet with magnetic field. The Cattaneo–Christov heat flux with convective boundary condition is accounted for. Shooting method is the instrumental for obtaining numerical solution of the transformed‐converted system of the mathematical models. Behavior of the determining thermo‐physical parameters on the velocity, temperature, skin friction, heat transfer rate, and finally isotherms are considered. The major relevant outcomes of the current investigation are that increment in Eyring‐Powell parameter uplifts flow velocity, while that peters out the fluid temperature. Enhanced values of the mixed convection parameter weakened the skin friction coefficient while it slightly strengthened the rate of heat transfer.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.444
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.022
GPT teacher head0.303
Teacher spread0.281 · 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