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Record W4406599456 · doi:10.28924/2291-8639-23-2025-17

Restarted Shooting Method Applied to Jeffery-Hamel Flow Problem

2025· article· en· W4406599456 on OpenAlexvenueno aff
Nawal Alzaid, Kholoud Alzahrani, H. O. Bakodah

Bibliographic record

VenueInternational Journal of Analysis and Applications · 2025
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Heat Transfer
Canadian institutionsnot available
Fundersnot available
KeywordsMathematicsFlow (mathematics)Trouble shootingShooting methodCalculus (dental)Mathematical analysisGeometryOrthodonticsMedicineEngineering

Abstract

fetched live from OpenAlex

In the current manuscript, an efficient numerical method based on coupling the restarted decomposition method and the shooting method has been implemented to tackle the nonlinear differential equation that describes blood flow in human arteries. A complete outline of the coupled method has been provided and further utilized on the generalized Jeffery-Hamel blood flow problem. In addition, the acquired computational results are contrasted with the numerical results of other computational approaches. Lastly, the efficacy of the devised numerical method is confirmed by the maximum error remainder and is reported through comparison tables and figures.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.901
Threshold uncertainty score0.320

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.004
GPT teacher head0.265
Teacher spread0.262 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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
Published2025
Admission routes1
Has abstractyes

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