The Development of the Complimentary Energy Decision Support Tool (CEDST) Platform, Solar Photovoltaic Calculator and Integration of other renewable and alternative energy calculators into CEDST
Bibliographic record
Abstract
Renewable and alternative energy technologies have become increasingly popular in Ontario over the last few years. Part of this increase has been from the Feed-In-Tariff incentive that pays Ontarians an amount per kWh generated by some of these technologies onto the central electricity grid. Between residential, commercial and agricultural settings, agriculture operations and locations offer an abundance of resources that make renewable energy systems attractive. The big question being asked by Ontario farmers is what renewable or alternative energy technology is best or most economical for their particular location and operation? The solution to that question is the Complimentary Energy Decision Support Tool (CEDST). This application combines Solar Photovoltaic, Wind Turbine, Geothermal, Anaerobic Digester, Solar Thermal and Energy Conservation calculators into one tool that compares the feasibility of each technology. This thesis specifically presents the development of the CEDST platform which is used as the delivery method for each of the individual calculators, the creation of the Solar Photovoltaic calculator and methodology behind determining if a solar photovoltaic system is a feasible solution, as well as, the integration of all the other individual calculators developed by the rest of the CESDT team into the CEDST platform.
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".