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Record W4408444077 · doi:10.5194/egusphere-egu25-2301

Closed-form expressions of vector gravity and magnetic field due to a rectangular disk.

2025· preprint· en· W4408444077 on OpenAlexaff
Hyoungrea Rim

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicGeophysics and Gravity Measurements
Canadian institutionsFuture Earth
Fundersnot available
KeywordsVector fieldPhysicsMagnetic fieldGravitational fieldClassical mechanicsGeometryTheoretical physicsMechanicsMathematicsQuantum mechanics

Abstract

fetched live from OpenAlex

In the case of applying magnetic exploration to detect underground man-made objects precisely, it is important to calculate magnetic responses analytically due to various shapes, such as one-dimensional line segments, 2D disk types, and 3D prismatic bodies. As part of these contributions, in this study, I derive the closed-form expressions of the magnetic field of one of 2D disk types, a rectangular disk. First, the gravitational potential due to a rectangular disk parallel to the x-y plane is defined by the two-dimensional surface integral. The vector gravity can be derived by differentiating the gravitational potential in each axial direction. The surface integrals that include the multiple square roots of the distance between observation points to the rectangular disk are required. Differentiating the vector gravity once more in each axial direction yields the gravity gradient tensor. For a causal body with constant magnetization, Poisson's relation is applied to convert the gravity gradient tensor to the magnetic field. The derived expressions of magnetic response are validated by comparing them with a three-dimensional rectangular prism with thin thickness. For the inclined rectangular disk, the magnetic fields are computed by transforming the observing coordinate system to the coordinate system affixed to the rectangular disk, and then the magnetic fields can be obtained by the inverse coordinate transformation.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.462
Threshold uncertainty score0.993

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)0.0010.000

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 head0.016
GPT teacher head0.234
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2025
Admission routes1
Has abstractyes

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