A Novel Coil-Based Overhauser Vector Magnetometer for the Automatic Measurement of Absolute Geomagnetic Total Field and Directions
Bibliographic record
Abstract
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”and 12.96”, 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”, 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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".