Diamond Experiment In the MagnetOSphere (DEIMOS): A Collisionless Shocks and Solar Wind Mission Concept for the Lunar Gateway
Bibliographic record
Abstract
Abstract In the scientific field of collisionless shocks, interplanetary space comprises a critical natural laboratory allowing the study of processes at spatial scales which are impossible to recreate in laboratories on Earth. Despite decades of research, key questions in the dynamics of collisionless shocks including energy transport and exchange remain unresolved due to instrumental limitations. With the return of humanity to the Moon and the upcoming construction of the Lunar Platform: Gateway (LOP‐G) space station, the possibility arises to study the pristine solar wind in unprecedented detail, with the space station potentially enabling significant power capacity and data rates which would be challenging to achieve on smaller unmanned spacecraft. The space station's location in a lunar halo orbit allows the study of the solar wind away from the contaminating influence of the terrestrial bow shock. Here we propose to utilize nitrogen‐vacancy (NV) diamond technology to combine magnetometer, temperature and plasma density measurements into a single instrument which can sample kHz‐range magnetic field with sensitivities on the order of <1e−5 nT, while also sounding the local plasma density and temperature. These capabilities will generate datasets which will contribute significantly to shock science, helping answer key outstanding questions in the field. Simultaneously, these observations will improve understanding of space weather dynamics, contribute to cross‐calibrating complementary missions, and probe the lunar exosphere. With the paucity of long‐term, high‐cadence, high‐sensitivity pristine solar wind datasets, the Diamond Experiment In the MagnetOSphere (DEIMOS) will fill a key need for the solar wind and collisionless shocks community.
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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 | 0.002 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".