Canadian Food Production Subsystem Designs for a Lunar Agriculture Module - Ground Test Demonstrator (LAM-GTD)
Bibliographic record
Abstract
The ability to produce fresh food in situ will be a beneficial addition to the future of sustainable lunar surface exploration, reducing reliance on traditional physiochemical life support systems and pre-packaged food supplies from Earth. To advance Controlled Environment Agriculture technologies and crew operations in preparation for a Lunar Agriculture Module, the Canadian Space Agency and the German Aerospace Center have conceptualized and progressed the design of a Lunar Agriculture Module - Ground Test Demonstrator. The purpose of this high-fidelity demonstrator would be to increase the technology readiness levels of all major greenhouse subsystems, simulate crew operations, and inform engineering requirements for an eventual lunar surface design. Canada is planning to contribute to the design of several key subsystems, including the Nutrient Delivery System, the Light Control System, the Versatile Assistant robotic arm, a Plant Health Monitoring System, and technologies that could improve confidence in the module's food safety processes. This paper outlines the progress made to date on these key subsystems and how our teams intend to use the Lunar Agriculture Module - Ground Test Demonstrator to prepare for the challenge of a Lunar Agricultural Module.
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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 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.016 | 0.004 |
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".