Low-noise permalloy ring cores for fluxgate magnetometers
Bibliographic record
Abstract
Abstract. Fluxgate magnetometers are important tools for geophysics and space physics, providing high-precision magnetic field measurements. Fluxgate magnetometer noise performance is typically limited by a ferromagnetic element that is periodically forced into magnetic saturation to modulate, or gate, the local magnetic field. The parameters that control the intrinsic magnetic noise of the ferromagnetic element remain poorly understood. Much of the basic research into producing low-noise fluxgate sensors was completed in the 1960s for military purposes and was never publicly released. Many modern fluxgates depend on legacy Infinetics S1000 ring cores that have been out of production since 1996 and for which there is no published manufacturing process. We present a manufacturing approach that can consistently produce fluxgate ring cores with a noise of ∼6–11 pT per square root hertz – comparable to many of the legacy Infinetics ring cores used worldwide today. As a result, we demonstrate that we have developed the capacity to produce the low-noise ring cores essential for high-quality, science-grade fluxgate instrumentation. This work has also revealed potential avenues for further improving performance, and further research into low-noise magnetic materials and fluxgate magnetometer sensors is underway.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".