Bibliographic record
Abstract
Global warming, the depletion of conventional energy reserves and the rising cost of electricity generation have sparked renewed interest in renewable wave energy within Canada and internationally. Significant advances in wave energy converters have been made in recent years, and there is a growing realization in many countries, particularly those in Europe, that these technologies will be ready for large scale deployments within the next five to ten years (ABP, 2004). Despite these recent developments, very little effort has been directed to quantifying and mapping wave energy resources in Canada in the past. This paper presents results from a recent study in which the wave energy resource in Canada’s Pacific and Atlantic waters is quantified by analysing a large quantity of data obtained from four sources: direct wave measurements; two wind-wave hindcasts of the North Atlantic; and a single hindcast of the Northeast Pacific. Each data source is described and the methods used to analyse the data sets are explained in detail. The derived wave power estimates, including their seasonal and spatial variability, are presented and discussed. Results obtained from the direct measurements and the wind-wave hindcasts are also compared. The paper also includes a review of the theoretical background required to estimate wave energy. The waters off Canada’s Pacific and Atlantic coasts are endowed with rich wave energy resources. The results presented here define the scale of these resources, as well as their significant spatial and seasonal variations.
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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) | 0.001 | 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".