The 2005 MARTE Robotic Drilling Experiment in Río Tinto, Spain: Objectives, Approach, and Results of a Simulated Mission to Search for Life in the Martian Subsurface
Bibliographic record
Abstract
The Mars Astrobiology Research and Technology Experiment (MARTE) simulated a robotic drilling mission to search for subsurface life on Mars. The drill site was on Peña de Hierro near the headwaters of the Río Tinto river (southwest Spain), on a deposit that includes massive sulfides and their gossanized remains that resemble some iron and sulfur minerals found on Mars. The mission used a fluidless, 10-axis, autonomous coring drill mounted on a simulated lander. Cores were faced; then instruments collected color wide-angle context images, color microscopic images, visible-near infrared point spectra, and (lower resolution) visible-near infrared hyperspectral images. Cores were then stored for further processing or ejected. A borehole inspection system collected panoramic imaging and Raman spectra of borehole walls. Life detection was performed on full cores with an adenosine triphosphate luciferin-luciferase bioluminescence assay and on crushed core sections with SOLID2, an antibody array-based instrument. Two remotely located science teams analyzed the remote sensing data and chose subsample locations. In 30 days of operation, the drill penetrated to 6 m and collected 21 cores. Biosignatures were detected in 12 of 15 samples analyzed by SOLID2. Science teams correctly interpreted the nature of the deposits drilled as compared to the ground truth. This experiment shows that drilling to search for subsurface life on Mars is technically feasible and scientifically rewarding.
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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 | 0.000 | 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) | 0.000 | 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".