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Record W2325157062 · doi:10.1190/segam2012-0874.1

Three dimensional finite-element forward modeling of electromagnetic data using potentials and unstructured meshes

2012· article· en· W2325157062 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Simulation and Numerical Methods
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsPolygon meshScalar (mathematics)Finite element methodTetrahedronElectromagnetic fieldComputational electromagneticsVector potentialScalar potentialBasis functionComputer scienceElectric fieldElectromagneticsMagnetic potentialMathematical analysisComputational sciencePhysicsGeometryElectronic engineeringClassical mechanicsMathematicsMagnetic fieldEngineering

Abstract

fetched live from OpenAlex

We deal with a finite-element solution to 3D geophysical electromagnetic problems. By decomposing the electric field into vector and scalar potentials, the system of equations is formed. The computational domain is subdivided into unstructured tetrahedral grids. Both edge and nodal basis functions are used to find approximate solutions for the potentials. The goal is to investigate how vector and scalar potentials, and therefore inductive and galvanic components, contribute to the resulting electric field.

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 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: none
Teacher disagreement score0.323
Threshold uncertainty score0.482

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.049
GPT teacher head0.295
Teacher spread0.246 · 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