Application of Non-Rectangular Hyperbola Model to the Lettuce and Beet Crops
Bibliographic record
Abstract
Long term manned missions such as a moon base or a trip to Mars will need a life support system with a high degree of closure. Such a life support system will therefore need to be based at least partially on bio-regenerative technologies. Higher plants will very likely be part of this system due to their ability to produce food, clean water, and regenerate the atmosphere. Due to the complexity of these systems, tools for optimization and control are required. In the framework of MELiSSA [1], where a predictive control strategy is foreseen for the different compartments of the loop, the knowledge of a first principles based model for plant growth is mandatory. The objectives of this paper are the implementation on EcosimPro [2] of a first principles model for photosynthesis at leaf level [3], the extension to canopy level with the help of an empirical light interception model [3], and finally a comparison of the final canopy model to experimental results obtained in the University of Guelph from single cultures of two MELiSSA candidate crops: beet and lettuce.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".