Status and Future of CSA’s Food Production Initiative - A Strategic Vision for Canada’s Future in Lunar Food Production
Bibliographic record
Abstract
In the next decade humans will return to the lunar surface. In contrast to historic campaigns, this next era will emphasize sustainable and collaborative exploration, allowing for a sustained human presence on the surface. Canada, along with international partners, are actively developing mission architectures and infrastructure intended to support and ensure a sustainable presence, while also supporting meaningful lunar science. Based on the 2019 Canadian Space Strategy, the Canadian Space Agency (CSA) established its Food Production Initiative tasked with advancing the state of controlled environment agriculture and advanced life support systems providing food and life-support services for lunar exploration missions. A key strategy of the Food Production Initiative was to consult directly with Canadian industry and academia through the establishment of the Food Production Topical Team. The Food Production Topical Team engaged over 40 leading experts in areas relevant to food production and terrestrial controlled environment agriculture. This group provided insight and recommendations to guide investment needed to address the mandate of the Food Production Initiative; to establish Canada as a leader in lunar food production and to provide one or more critical systems to an international lunar surface food system partnership. In this context, a full-scale lunar food production system was proposed, which would significantly support international efforts to expand human presence beyond low-Earth orbit and help secure the future of the Canadian astronaut program. Mid-term milestones towards this possible flagship level contribution were proposed including a small lunar plant growth payload and a high-fidelity bioregenerative life support testbed. All proposed activities should create tangible socio-economic benefits, including advancing food security in Canada's northern and remote communities. This paper presents the findings and recommendations of the Food Production Topical Team as well as the ensuing vision statement, strategy and related infrastructure/ hardware roadmap from subsequent CSA consultation and analysis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".