Raman characterization of terrestrial analogs from the AMADEE‐18 astronaut simulated mission using the ExoMars RLS simulator: Implications for Mars
Bibliographic record
Abstract
Abstract Between February 1 and February 28, 2018, the Austrian Space Forum, in cooperation with research teams from 25 nations, conducted the AMADEE‐18 mission—a human‐robotic Mars expedition simulation in the Dhofar region in the Sultanate of Oman. As a part of the AMADEE‐18 simulated Mars human exploration mission, the Remote Science Support team investigated the Dhofar area (Oman) to qualify it as a potential Mars analog site. The motivation of this research was to study and register selected samples collected by the analog astronauts during the AMADEE‐18 mission with the European Space Agency (ESA) ExoMars Raman Laser Spectrometer (RLS) simulator, compare the results with standard laboratory measurements, and establish the implication of the results to the future ESA ExoMars mission. The Raman measurements identified minerals such as carbonates (calcite and dolomite), feldspar and plagioclase (albite, anorthite, orthoclase, and sanidine), Fe‐oxides (goethite, hematite, and magnetite), and Ti‐oxide (anatase), each relevant to planetary exploration. As we have presented here, Raman spectroscopy is a powerful tool for detecting the presence of organic molecules, particularly by analyzing the principal vibration of CC and CH bonds. It has also been shown that portable Raman spectroscopy is a relevant tool for in situ field studies such as those conducted during extra‐vehicular activities (EVA) in simulated missions like the AMADEE‐18 and the future AMADEE‐2020 campaign.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".