Characterizing Lake Ontario Marine Renewable Energy Resources
Bibliographic record
Abstract
AbstractLake Ontario, the smallest in surface area among the Great Lakes, is the last lake in the Great Lakes' hydrologic chain. In this study, Lake Ontario's marine renewable energy resources are characterized. The historical wave records reveal up to 8 m significant wave heights in Lake Ontario's eastern basin. Furthermore, the lake's historical water level data indicate that storm surges can get as large as 1 m near Port Weller and Burlington. The storms of November 13, 2003, and January 30, 2008, are estimated to produce a total theoretical potential energy of ~25 GWh. The lake-wide monthly mean wave power for the selected year 2011 is at its peak in October and November, exceeding 10 kW/m. On the other hand, it is estimated to be around 1 kW/m during late spring and summer. The present work is part of an extensive study attempting to characterize marine renewable energy resources for the entire Great Lakes and follows the recently published works on Lake Erie and Lake Michigan (Farhadzadeh et al., 2017; Velioglu Sogut et al., 2018). It is also the first study elaborating on the characterization of Lake Ontario's marine renewable energy resources.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| 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) | 0.003 | 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".