A New Magnetic Field Activity Proxy for Mars From MAVEN Data
Bibliographic record
Abstract
Abstract The identification of magnetically quiet or noisy observations is important for data selection in a wide range of studies, including crustal field modeling and investigations of the ionosphere. However this remains a challenge when studying the magnetic field of Mars, as no continuous magnetic activity index is available. Such indices are widely used for studies of Earth's magnetic field, and they are largely based on data from ground observatories. We suggest a martian magnetic activity proxy based on satellite data, from the Mars Atmosphere and Volatile EvolutioN spacecraft (MAVEN). MAVEN has been in orbit since November 2014, providing measurements of the magnetic field that extend those from the Mars Global Surveyor mission. The proxy uses the magnitude of the interplanetary magnetic field upstream of the bow shock and is motivated by the correlation of the interplanetary magnetic field amplitude with the nightside magnetic field at 150‐ to 600‐km altitude, measured on the same MAVEN orbit. We demonstrate the utility of the proxy, by producing a model of the surface crustal field in a previously mapped low‐amplitude region in the vicinity of the InSight landing site. The proposed proxy successfully separates quiet and noisy data and will facilitate MAVEN data selection for higher‐resolution crustal field models. Other applications include data selection for magnetic sounding studies using the InSight magnetometer, or studies of the ionosphere. The deployment of a ground‐based magnetometer by InSight will also allow the refinement of the proxy, using simultaneous satellite and surface magnetic field measurements.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".