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Record W2010475796 · doi:10.1186/bf03351646

Magnetic distortion of the magnetotelluric tensor: a numerical study

2014· article· en· W2010475796 on OpenAlexafffund
Alok Agarwal, J. T. Weaver

Bibliographic record

VenueEarth Planets and Space · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysical and Geoelectrical Methods
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Victoria
KeywordsDistortion (music)MagnetotelluricsTensor (intrinsic definition)Magnetic fieldPhysicsMathematicsGeometryElectrical resistivity and conductivity

Abstract

fetched live from OpenAlex

Decomposition of the magnetotelluric (MT) tensor when the electric field alone is subject to local galvanic distortion has received much attention in recent years. Recently some authors have extended such procedures to include the effects of the associated magnetic field distortion as well. With the aid of a three-dimensional modelling program the validity of the assumptions made in these analyses have been examined by considering the response over a range of periods of a small conductive cube at the surface of the earth and near a two-dimensional fault. The study indicates that the inclusion of magnetic distortion is necessary and important at short periods when induction occurs in the anomaly itself, but that the elements defining the magnetic distortion matrix become complex at such periods so that the assumptions underlying the theory are no longer valid. At longer periods the magnetic distortion matrix does become real and frequency-independent and therefore determinate, but its effect on the response becomes insignificant compared with that due to electric distortion. At these longer periods the phases of the regional impedances and the ratios of the electric distortion parameters are correctly recovered whether magnetic distortion is present or not. Calculations were repeated for a resistive cube, and also for a highly resistive region beneath the surface layer, with no significant enhancement of magnetic distortion. It is concluded that, at least for such models, inclusion of magnetic distortion in decompositions of the MT tensor does not, in general, offer any improvement over the conventional decompositions in which only distortion of the electric field is taken into account.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.524
Threshold uncertainty score0.578

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 head0.007
GPT teacher head0.196
Teacher spread0.189 · 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

Citations10
Published2014
Admission routes2
Has abstractyes

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