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Record W3194424468 · doi:10.4236/jamp.2021.98125

Resistance Matrix for an Anisotropic Hall Plate with Multiple Extended Asymmetric Contacts on the Boundary

2021· article· en· W3194424468 on OpenAlexaff
Dorel Homentcovschi, O. Radu, Bruce T. Murray

Bibliographic record

VenueJournal of Applied Mathematics and Physics · 2021
Typearticle
Languageen
FieldEngineering
TopicMagnetic Field Sensors Techniques
Canadian institutionsEaglePicher (Canada)
Fundersnot available
KeywordsVan der Pauw methodIsotropyAnisotropyCondensed matter physicsMatrix (chemical analysis)Magnetic fieldMaterials scienceHall effectPerpendicularMagnetoresistanceMatrix methodElectrical resistance and conductanceMathematical analysisPhysicsGeometryMathematicsComposite materialOptics

Abstract

fetched live from OpenAlex

The electrical properties of magnetic sensing devices fabricated from anisotropic materials are not easily extracted. Here we present a method for determining the resistance matrix for an anisotropic device with multiple electrical contacts placed in a perpendicular magnetic field. By using the methods developed by Van der Pauw and Wasscher, the analysis for the anisotropic system is reduced to the equivalent problem for an isotropic sample, which can then be solved using methods developed previously. As a result, the method works in the case of structures with an arbitrary number of asymmetric extended contacts at large magnetic field strength. In addition to the extraction of nonisotropic resistivities, the resistance matrix can be used to analyze the Hall effect for anisotropic plates.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.014
GPT teacher head0.232
Teacher spread0.218 · 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
Published2021
Admission routes1
Has abstractyes

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