Enhancing solar insolation in agricultural greenhouses by adjusting its orientation and shape
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A controlled environment greenhouse requires a large amount of heating during the winter months, which is conventionally supplied by environmentally damaging fossil fuels. To lessen the detrimental effect of fossil fuels on the environment, it is beneficial to use clean solar energy for heating these greenhouses. This paper aims to enhance solar insolation in a greenhouse located in Toronto, Ontario by manipulating greenhouse orientations, roof inclinations, and greenhouse shapes. Different greenhouse models were designed on SketchUp software and then simulated in TRNSYS software to determine the pattern of solar insolation available on different greenhouse models. Greenhouse orientation considered for this study included east-west orientation, north-south orientation, and distinct angles between these orientations. Different roof inclinations of 15°, 30°, 45°, and 60° were examined to observe the pattern of solar insolation availability on the greenhouse roofs. Further to this, typical shapes of a greenhouse (i.e., even, uneven, vinery, semi-circular, elliptical or arch, single span, and quonset) were also investigated to determine solar insolation on greenhouse surfaces.
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.
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 | 0.001 | 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 it