The Sample Handling System for the Mars Icebreaker Life Mission: From Dirt to Data
Bibliographic record
Abstract
The Mars Icebreaker Life mission will search for subsurface life on Mars. It consists of three payload elements: a drill to retrieve soil samples from approximately 1 m below the surface, a robotic sample handling system to deliver the sample from the drill to the instruments, and the instruments themselves. This paper will discuss the robotic sample handling system. Collecting samples from ice-rich soils on Mars in search of life presents two challenges: protection of that icy soil--considered a "special region" with respect to planetary protection--from contamination from Earth, and delivery of the icy, sticky soil to spacecraft instruments. We present a sampling device that meets these challenges. We built a prototype system and tested it at martian pressure, drilling into ice-cemented soil, collecting cuttings, and transferring them to the inlet port of the SOLID2 life-detection instrument. The tests successfully demonstrated that the Icebreaker drill, sample handling system, and life-detection instrument can collectively operate in these conditions and produce science data that can be delivered via telemetry--from dirt to data. Our results also demonstrate the feasibility of using an air gap to prevent forward contamination. We define a set of six analog soils for testing over a range of soil cohesion, from loose sand to basalt soil, with angles of repose of 27° and 39°, respectively. Particle size is a key determinant of jamming of mechanical parts by soil particles. Jamming occurs when the clearance between moving parts is equal in size to the most common particle size or equal to three of these particles together. Three particles acting together tend to form bridges and lead to clogging. Our experiments show that rotary-hammer action of the Icebreaker drill influences the particle size, typically reducing particle size by ≈ 100 μm.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".