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Record W3156856459 · doi:10.1119/10.0003508

Magnetic diffusion, inductive shielding, and the Laplace transform

2021· article· en· W3156856459 on OpenAlexafffund
Alexander E. Krosney, Michael L. Lang, Jakob J. Weirathmueller, Christopher P. Bidinosti

Bibliographic record

VenueAmerican Journal of Physics · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicExperimental and Theoretical Physics Studies
Canadian institutionsUniversity of Winnipeg
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhysicsElectromagnetic shieldingLaplace transformMagnetic fieldDiffusionPercolation (cognitive psychology)Computational physicsMechanicsMathematical analysisQuantum mechanicsMathematics

Abstract

fetched live from OpenAlex

In the quasistatic limit, a time-varying magnetic field inside a conductor is governed by the diffusion equation. Despite the occurrence of this scenario in many popular physics demonstrations, the concept of magnetic diffusion appears not to have garnered much attention itself as a subject for teaching. We employ the model of a thin conducting tube in a time-varying axial field to introduce magnetic diffusion and connect it to the related phenomenon of inductive shielding. We describe a very simple apparatus utilizing a wide-band Hall-effect sensor to measure these effects with a variety of samples. Quantitative results for diffusion time constants and shielding cutoff frequencies are consistent with a single, sample-specific parameter given by the product of the tube radius, thickness, and electrical conductivity. The Laplace transform arises naturally in regard to the time and frequency domain solutions presented here, and the utility of the technique is highlighted in several places.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

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 studies0.0000.002
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0010.001
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 head0.003
GPT teacher head0.221
Teacher spread0.217 · 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 designTheoretical or conceptual
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

Citations3
Published2021
Admission routes2
Has abstractyes

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