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Record W2046862887 · doi:10.1139/p05-002

Stability of mixed-convection boundary-layer flow on a porous wedge

2005· article· en· W2046862887 on OpenAlexvenueno aff
Takashi Watanabe, Hideo Taniguchi, S. MINATO

Bibliographic record

VenueCanadian Journal of Physics · 2005
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsnot available
Fundersnot available
KeywordsMechanicsPhysicsLaminar flowOrdinary differential equationBoundary layerDifferential equationFlow (mathematics)Wedge (geometry)BuoyancyCombined forced and natural convectionConvectionThermodynamicsNatural convectionOptics

Abstract

fetched live from OpenAlex

A theoretical analysis is presented of the stability characteristics of laminar forced–free mixed-convection boundary-layer flow past an isothermal wedge with uniform suction or injection. The nonsimilar boundary-layer equations for the basic steady flow are solved numerically with a difference-differential scheme in combination with an iterative method for solving the resulting ordinary differential equations. The disturbance equations are then solved numerically on the basis of linear stability theory. The neutral stability curves and the disturbance amplitude of the velocity component and of the temperature are presented graphically for values of the buoyancy parameter ζ, the pressure-gradient parameter m, and the suction/injection parameter X. The results indicate the important role of the suction/injection parameter on the characteristics of both basic flow and disturbance flow. PACS No.: 47.20.–k

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.188
Teacher spread0.178 · 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

Citations0
Published2005
Admission routes1
Has abstractyes

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