Detecting Upward Directed Charged Particle Fluxes in the Mars Science Laboratory Radiation Assessment Detector
Bibliographic record
Abstract
The Mars Science Laboratory rover Curiosity, operating on the surface of Mars, is exposed to radiation fluxes from above and below. Galactic Cosmic Rays travel through the Martian atmosphere, producing a modified spectrum consisting of both primary and secondary particles at ground level. These particles produce an upward directed secondary particle spectrum as they interact with the Martian soil. Here we develop a method to distinguish the upward and downward directed particle fluxes in the Radiation Assessment Detector (RAD) instrument, verify it using data taken during the cruise to Mars, and apply it to data taken on the Martian surface. We use a combination of Geant4 and Planetocosmics modeling to find discrimination criteria for the flux directions. After developing models of the cruise phase and surface shielding conditions, we compare model‐predicted values for the ratio of upward to downward flux with those found in RAD observation data. Given the quality of available information on Mars Science Laboratory spacecraft and rover composition, we find generally reasonable agreement between our models and RAD observation data. This demonstrates the feasibility of the method developed and tested here. We additionally note that the method can also be used to extend the measurement range and capabilities of the RAD instrument to higher energies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".