Potential for Recovery of Plant Macronutrients from Space Habitat Wastes for Salad Crop Production
Bibliographic record
Abstract
Crop production in space habitats is currently under consideration as part of an advanced life support system. The scenarios for crop production vary depending on the mission objectives. For a mission scenario such as the International Space Station (ISS), current efforts propose only salad crop production. However in order to grow salad crops, there is a need for plant nutrients (elements) such as N, P, K, Ca, etc., which constitutes about 10% of dry weight of the plant. Nitrogen and potassium are the major elements needed by salad crops and currently require resupply on Station. However, it is feasible that these macronutrients could be recovered through the waste materials generated by the crew. The proposed concepts are non-oxidative and simple in design. This paper considers the potential for reclaiming macronutrients from urine and gray water concentrates from water recovery systems. The potential gains from reducing resupply from use of urine and gray water concentrates are listed. A detailed discussion of the processing means to recover the nutrients is given.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".