Inukshuk Landed Robotic Canadian Mission to Mars using a Miniature Sample Analysis Lab for Planetary Mineralogy and Microbiology
Bibliographic record
Abstract
This paper discusses the Inukshuk landed rover mission to Mars that is currently undergoing the Phase 0 mission study for the Canadian Space Agency. The Inukshuk landed rover mission addresses key science themes for planetary exploration; focusing on the search for hydrated mineralogy and subsurface water sites that can provide evidence of past or present life. New exploration and science will be accomplished using an innovative tethered combination of a small rover and a self-elevating sky-cam aerostat. The elevating visible (VIS) imager, at about 10 m altitude, will provide an informative high-resolution 2-D view of the rover below and surrounding terrain to greatly assist the semi-autonomous navigation of the rover around obstacles and selection of sites for detailed subsurface exploration. The solar-powered rover will employ MDA expertise in robotics and drilling with MPB's expertise in miniature infrared (IR) spectrometers and fiber-optic sensors to provide subsurface analysis of mineralogy and temperature distributions at depths to about 1 m. Mission cost effectiveness is achieved through a synergistic instrument suite based on advanced but mature miniaturization technologies that enable high IR spectral measurement performance with minimal mass and power. Insitu systematic sample analysis at depths to about 1 m will be performed using a monolithic fiber-optic coupled probe integrated directly with the tethered mole driller. For space-based systems, the important drivers are reliability, power consumption, mass and simplicity of operation. MPB has advanced its patented IOSPEC technology for miniature integrated IR spectrometers to provide high performance comparable to large laboratory spectrometers but in a very compact and ruggedized footprint weighing under 2.0 kg. Inukshuk sample analysis will employ the data synergy provided by a miniature suite of high-performance instruments, including IR reflection between 0.8 and 4.5 microns at about 4 nm resolution, microscopic VIS colour imaging to 1 μm spatial resolution, and complementary IR Raman spectroscopy between 500 and 3500 cm-1 for direct C-C biological detection. The combined data can, for the first time, directly and unambiguously detect H2O and determine its state (ice/liquid/structural), distinguish key mineral species (including those associated with favorable habitats for microbial activity) and determine their hydration states, as well as detect and differentiate various C-H and C-C molecular structures for astrobiological investigations.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.035 | 0.009 |
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".