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Record W2234471438 · doi:10.4271/2001-01-2350

Potential for Recovery of Plant Macronutrients from Space Habitat Wastes for Salad Crop Production

2001· article· en· W2234471438 on OpenAlexaff
Kanapathipillai Wignarajah, Suresh Pisharody, Mark Moran, John W. Fisher

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicPhosphorus and nutrient management
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsCropProduction (economics)HabitatEnvironmental scienceCrop productionSpace (punctuation)AgronomyAgricultureComputer scienceBiologyEcology

Abstract

fetched live from OpenAlex

<div class="htmlview paragraph">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.</div> <div class="htmlview paragraph">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.</div>

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.950
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.008
GPT teacher head0.218
Teacher spread0.209 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2001
Admission routes1
Has abstractyes

Explore more

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