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Record W2981315295 · doi:10.1139/cjp-2019-0380

Theoretical treatment of bio-convective Maxwell nanofluid over an exponentially stretching sheet

2019· article· en· W2981315295 on OpenAlexvenueno aff
Muhammad Naveed Khan, S. Nadeem

Bibliographic record

VenueCanadian Journal of Physics · 2019
Typearticle
Languageen
FieldEngineering
TopicNanofluid Flow and Heat Transfer
Canadian institutionsnot available
Fundersnot available
KeywordsNanofluidNusselt numberSherwood numberPhysicsMechanicsShooting methodParasitic dragBoundary value problemMass fluxConvectionMass transferClassical mechanicsThermodynamicsBoundary layerHeat transferReynolds number

Abstract

fetched live from OpenAlex

The heat and mass transfer of unsteady two-dimensional flow of a bio-convective non-Newtonian Maxwell nanofluid past an exponentially stretching sheet is presented. A viscous dissipation and external magnetic field along multiple slip conditions and chemical reactions are incorporated. The governing partial differential equations are reduced to the system of ordinary differential equations by applying suitable transformations. Using the bvp4c -shooting technique, we were able to solve the boundary value problem. The influence of the obtained parameters are deliberated graphically on the velocity, concentration, temperature, and microorganism profile. The tabulated values of skin friction, Nusselt number, mass flux rate, and microorganism rate along various parameters are computed and examined. The findings show that the value of the skin friction, Nusselt number, Sherwood number, and microorganism number decline due to enhancement in the time relaxation parameter.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.197
Teacher spread0.190 · 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 designTheoretical or conceptual
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

Citations57
Published2019
Admission routes1
Has abstractyes

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