The SDEMMA model for galactic cosmic ray and its dosimetric application
Bibliographic record
Abstract
Introduction Future crewed missions to Mars will encounter substantially elevated radiation levels compared to low Earth orbit operations. To address this challenge, we present the Space-Dependent Energetic cosmic ray Modulation using MAgnetic spectrometer (SDEMMA) model, a novel framework for modeling galactic cosmic ray (GCR) dynamics in deep-space environments. Methods The model employs stochastic differential equations with outer boundary conditions derived from contemporary local interstellar spectrum models. Time-dependent diffusion and drift coefficients were optimized through Markov Chain Monte Carlo parameter fitting against 2006-2019 observational data from the space-borne magnetic spectrometers of AMS-02 and PAMELA. Results SDEMMA extends GCR spectral calculations to radial positions beyond 1.0 AU, explicitly resolving radial gradients under diverse heliospheric conditions. The framework provides spatiotemporally resolved GCR spectra for charge numbers Z=1–28 at rigidities >0.2 GV, covering the inner heliosphere between Earth and Mars and currently the 2006-2019 epoch. Discussion Implementation demonstrates the model's operational utility: dose equivalent rates behind 30 g/cm2 polyethylene shielding during a flux minimum range from 14-17 cSv/yr, with variance attributable to quality factor selection.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".