The MARS2013 Mars Analog Mission
Bibliographic record
Abstract
We report on the MARS2013 mission, a 4-week Mars analog field test in the northern Sahara. Nineteen experiments were conducted by a field crew in Morocco under simulated martian surface exploration conditions, supervised by a Mission Support Center in Innsbruck, Austria. A Remote Science Support team analyzed field data in near real time, providing planning input for the management of a complex system of field assets; two advanced space suit simulators, four robotic vehicles, an emergency shelter, and a stationary sensor platform in a realistic work flow were coordinated by a Flight Control Team. A dedicated flight planning group, external control centers for rover tele-operations, and a biomedical monitoring team supported the field operations. A 10 min satellite communication delay and other limitations pertinent to human planetary surface activities were introduced. The fields of research for the experiments were geology, human factors, astrobiology, robotics, tele-science, exploration, and operations research. This paper provides an overview of the geological context and environmental conditions of the test site and the mission architecture, in particular the communication infrastructure emulating the signal travel time between Earth and Mars. We report on the operational work flows and the experiments conducted, including a deployable shelter prototype for multiple-day extravehicular activities and contingency situations.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".