Energy consumption and commercial applications of liquid foam insulation technology for greenhouses
Bibliographic record
Abstract
It is well known fact that operating a commercial greenhouse in northern Latitudes requires large amounts of energy. As energy prices continue to fluctuate, it is critically important to provide growers with a tool that gives them greater control of their micro-climate. Sunarc of Canada has developed an energy saving system for commercial greenhouse growers. The liquid foam insulating system was installed at site 1 over an area of 14,700 ft² (Chatam, ON, Canada), as well as at site 2 (Leamington, ON, Canada) over an area of 43,000 ft². Both facilities were monitored for energy use during the 2007 winter period. Night-time energy savings ranged from above 60% to below 10% depending on outdoor temperatures with greater savings occurring during colder outdoor temperatures. Monthly average night-time energy savings resulted in values from February, March and April 2007 of 46.6, 42, and 32.3% respectively. Following initial commercial testing the liquid foam system was reengineered to improve and optimize operations, reduce fill time, and improve liquid foam formulas. The new system was installed at site 3 (Laval, QC, Canada) as a demonstration unit. The company is presently negotiating international distribution writes with several partners.
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 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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".