Climate change impacts on Ontario wind power resource
Bibliographic record
Abstract
Abstract Background The availability and reliability of wind power depend largely on current and future climate conditions, which may vary in the context of climate change. A high resolution regional climate model (PRECIS) was used for dynamic downscaling of the future wind speed over Ontario. The changes of wind power density and power production were further investigated through case studies. Results The spatial pattern and the magnitude of wind speed from PRECIS simulation, Wind Energy Atlas and the observation indicated a successful climate simulation. Climate modelling indicated that there would be a decrease of up to 5% in wind speed over southern Ontario from present to the period of 2071–2100. It was showed in the case studies that the changes of wind power production were not in proportion to the changes of average wind speed, due to the variations of wind speed distribution. Conclusion The decrease of projected wind speed would be more intense in A2 than in B2 scenario, showing statistically significant differences in the grid cell mean wind speed. The changes of wind power production may not be in proportion to the changes of average wind speed. It would be reasonable to develop onshore or offshore wind energy industry around Georgian Bay and James Bay, considering the projected increasing wind speeds within these areas.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".