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Record W4387587537 · doi:10.1109/tmech.2023.3319396

A Novel Coil-Based Overhauser Vector Magnetometer for the Automatic Measurement of Absolute Geomagnetic Total Field and Directions

2023· article· en· W4387587537 on OpenAlexaff
Jian Ge, Hong Yu, Wang Luo, Y.Q. Shen, Haobin Dong, Zheng Liu

Bibliographic record

VenueIEEE/ASME Transactions on Mechatronics · 2023
Typearticle
Languageen
FieldEngineering
TopicMagnetic Field Sensors Techniques
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersNational Natural Science Foundation of China
KeywordsEarth's magnetic fieldMagnetometerNuclear magnetic resonancePhysicsField (mathematics)Nuclear Overhauser effectAbsolute (philosophy)Magnetic fieldMathematicsNuclear magnetic resonance spectroscopyQuantum mechanicsPhilosophy

Abstract

fetched live from OpenAlex

The absolute measurement of geomagnetic parameters can be applied directly not only in magnetic navigation and target detection but also in the correction of relative measurement. The absolute geomagnetic measurement generally adopts a combined measurement mode. Owing to differences in the principles of different magnetometers, it is difficult to comprehensively apply absolute data. To address this problem, we propose a novel automatic measurement model for the absolute geomagnetic total field and directions. Gearing toward field mobile measurement, we developed an integrated vector magnetometer using an improved Overhauser total-field sensor and a miniaturized spherical magnetic field generator. Component test results obtained for an artificial magnetic field generator show that the expanded uncertainty of Overhauser sensor with reduced dimensions was still below 0.10 nT, and the magnetic gradient formed by the applied bias fields had no negative effect on the performance of Overhauser sensor. In overall tests conducted in geomagnetic observatories, between the proposed magnetometer and a standard manually operated declination–inclination magnetometer, the differences of inclination and declination were only 14.40 <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">”</i> and 12.96 <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">”</i> , respectively. The noises of total field, horizontal component, and declination measured by the proposed magnetometer were 0.02 nT, 0.08 nT, and 0.47 <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">”</i> , respectively, which are much lower than those of a state-of-the-art standard variometer. The proposed magnetometer is expected to be applied to unattended monitoring of geomagnetic field for the geomagnetic navigation, exploration of weak magnetic anomaly produced by the deep mineral resources, automatic remote detection of moving magnetic targets, fine-scale characterization of the plate tectonics, etc.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.887
Threshold uncertainty score0.725

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)0.0000.000

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 head0.019
GPT teacher head0.228
Teacher spread0.209 · 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 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

Citations3
Published2023
Admission routes1
Has abstractyes

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