Combined Spectroscopic Analysis of Terrestrial Analogs from a Simulated Astronaut Mission Using the Laser-Induced Breakdown Spectroscopy (LIBS) Raman Sensor: Implications for Mars
Why this work is in the frame
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Bibliographic record
Abstract
One of the primary objectives of planetary exploration is the search for signs of life (past, present, or future). Formulating an understanding of the geochemical processes on planetary bodies may allow us to define the precursors for biological processes, thus providing insight into the evolution of past life on Earth and other planets, and perhaps a projection into future biological processes. Several techniques have emerged for detecting biomarker signals on an atomic or molecular level, including laser-induced breakdown spectroscopy (LIBS), Raman spectroscopy, laser-induced fluorescence (LIF) spectroscopy, and attenuated total reflectance Fourier transform infrared (ATR FT-IR) spectroscopy, each of which addresses complementary aspects of the elemental composition, mineralogy, and organic characterization of a sample. However, given the technical challenges inherent to planetary exploration, having a sound understanding of the data provided from these technologies, and how the inferred insights may be used synergistically is critical for mission success. In this work, we present an in-depth characterization of a set of samples collected during a 28-day Mars analog mission conducted by the Austrian Space Forum in the Dhofar region of Oman. The samples were obtained under high-fidelity spaceflight conditions and by considering the geological context of the test site. The specimens were analyzed using the LIBS-Raman sensor, a prototype instrument for future exploration of Mars. We present the elemental quantification of the samples obtained from LIBS using a previously developed linear mixture model and validated using scanning electron microscopy energy dispersive spectroscopy. Moreover, we provide a full mineral characterization obtained using ultraviolet Raman spectroscopy and LIF, which was verified through ATR FT-IR. Lastly, we present possible discrimination of organics in the samples using LIF and time-resolved LIF. Each of these methods yields accurate results, with low errors in their predictive capabilities of LIBS (median relative error ranging from 4.5% to 16.2%), and degree of richness in subsequent inferences to geochemical and potential biochemical processes of the samples. The existence of such methods of inference and our ability to understand the limitations thereof is crucial for future planetary missions, not only to Mars and Moon but also for future exoplanetary exploration.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 it