Mechanical Subsystem Design and Space Qualification of a Dual-Sensor Multispectral Imager for Lunar Rover Applications
Bibliographic record
Abstract
As part of the human return to the Moon, there is great scientific interest in exploration of the lunar south pole. A novel dual-sensor multispectral imager has been developed at the University of Western Ontario that can capture images of geological targets in multiple wavelengths, permitting spectral interpretation. This instrument would be mounted to the mast of a future Canadian lunar rover. A proof-of-concept prototype was previously tested.\nIn this work, the next-generation compact design was developed to withstand the conditions of spaceflight. The design is shown through simulation to survive the launch vibration environment and thermomechanical deformation during the lunar night. To predict the expected temperatures, a lunar regolith thermal model was developed and validated for accuracy at the lunar poles, leveraging newer data from the LRO mission. Finally, a coregistration pipeline for the multispectral data from the instrument was developed and validated for combining data from non-identical sensors.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".