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Record W2612877363

Амплитудно-фазовая коррекция кривых магнитотеллурического зондирования

2011· article· ru· W2612877363 on OpenAlexaboutno aff
Ido Feldman, Е. Ю. Ермолин

Bibliographic record

VenueЗаписки Горного Института · 2011
Typearticle
Languageru
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsData processingAmplitudeNoise (video)Electrical impedanceBasis (linear algebra)Tensor (intrinsic definition)Computer scienceData qualityPhysicsElectrical engineeringMathematicsEngineeringArtificial intelligenceOpticsGeometry
DOInot available

Abstract

fetched live from OpenAlex

The regularities of the amplitudes and phases connections of magnitotelluric (MT) impedance tensor components for 1D, 2D and 3D geoelectrical synthetic models have been considered. The amplitude-phase correction allows to improve the quality of data processing results both for the main and for the additional impedances. It also gives a possibility to suppress biased data for noise pollution data. Recommendations on accuracy rising of determination of tensor impedance components in the MT-data processing have been defined on the base of found regularities. Examples of processing of field MT-data received on the basis of MTU equipment by «Phoenix Geophysics Ltd» (Canada) have been considered.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0120.005

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 head0.051
GPT teacher head0.214
Teacher spread0.163 · 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
Published2011
Admission routes1
Has abstractyes

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