The configuration optimization of the plants in vertical farming by 3D modeling
Bibliographic record
Abstract
Abstract Vertical farming, a terminology in landscape architecture, is designed to cater for the demand of vegetation under the impact of excessive exploid of land, especially in densely-populated areas. The study takes vertical farming in Singapore as an example, applies 3D modeling to investigate the effect of different arrangement patterns on plant light absorption in vertical farms, and proposes some measures. Through the 3D simulation process, each square of the soil for planting can be quantified in sunlight-exposure hour. The experiment result shows that configuration with an array piling up is judicious and feasible for greenhouse growth, especially for commercial usages. Different configurations of plants influence the efficiency of utilizing sunlight, and there is a better layout for a particular site in different usages. For some cities far away from tropical areas, this configuration may alleviate the impact of lacking sunlight exposure. The main advantage of vertical farms is efficiency, as they require less land and water with more yield per acre compared to conventional farms.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".