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Record W1997510887 · doi:10.1002/pamm.200700094

Surface stability of nonlinear magnetoelastic solids

2007· article· en· W1997510887 on OpenAlexaff
Mélanie Otténio, Michel Destrade, Ray W. Ogden

Bibliographic record

VenuePAMM · 2007
Typearticle
Languageen
FieldEngineering
TopicVibration Control and Rheological Fluids
Canadian institutionsToronto Metropolitan University
FundersCentre National de la Recherche ScientifiqueUniversity of Glasgow
KeywordsBifurcationNonlinear systemHomogeneousStability (learning theory)Elasticity (physics)MagnetismBifurcation theorySurface (topology)Boundary value problemNonlinear elasticityPlane (geometry)Boundary (topology)Materials scienceCoupling (piping)Parameter spaceMathematical analysisMechanicsMathematicsPhysicsCondensed matter physicsGeometryThermodynamicsComputer scienceComposite material

Abstract

fetched live from OpenAlex

Abstract The present paper proposes to identify surface stability when a magnetoelastic half‐space is subjected to a pure homogeneous pre‐deformation and to a magnetic field normal to its (plane) boundary. Clearly, the aim is to find the critical stretch ratio beyond which surface instabilities may develop, or in other words, to establish a bifurcation criterion based on the incremental static solution of the boundary value problem. We want to analyse how the presence of a coupling between magnetism and nonlinear elasticity modify the conditions of stability. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
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
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
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 head0.013
GPT teacher head0.219
Teacher spread0.207 · 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 designBench or experimental
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
Published2007
Admission routes1
Has abstractyes

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