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Proton magnetometer sensor design and its performance

2021· article· en· W3154067173 on OpenAlexaboutno aff
Ning Ma, Shudong Chen, Shuang Zhang

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAtomic and Subatomic Physics Research
Canadian institutionsnot available
Fundersnot available
KeywordsMagnetometerProtonSIGNAL (programming language)Electromagnetic shieldingNuclear magnetic resonanceMagnetic fieldElectromagnetic coilPhysicsElectrical engineeringComputer scienceNuclear physicsEngineering

Abstract

fetched live from OpenAlex

Abstract The proton sensor is an important part of the proton magnetometer, which is mainly responsible for generating a polarizing magnetic field and receiving induced signals. This paper presents the design scheme of the proton sensor, including the selection of the internal coil structure of the sensor, the selection of the internal solution, and the design of the sensor shielding layer. Then introduces the proton sensor of the Canadian GSM-19T proton magnetometer, which is one of the world’s leading proton magnetometers. And the performance of the two sensors is compared and analyzed by designing sensor performance test experiment. The experimental results show that the initial amplitude of the test signal of the proton sensor is 2.2V, and the signal decay time constant is 0.86s, the performance is similar to that of the Canadian proton sensor.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.185
Threshold uncertainty score0.704

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 studies0.0000.001
Scholarly communication0.0000.001
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 head0.022
GPT teacher head0.233
Teacher spread0.211 · 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 designBench or experimental
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 routes1
Has abstractyes

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