Perspectives on offshore wind farms development in Great Lakes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Our atmosphere is overloading with carbon dioxide and other global warming emissions due to human activities. It causes a web of significant and harmful impacts. Renewable energy resources produce little to no global warming emissions. To date, most of the existing offshore wind farms have been deployed in shallow ocean-coastal areas. The salinity of the ocean averages approximately 35 percent. The Great Lakes with freshwater have shown high potential for installing offshore wind farms, and significant advantages. In this study, the potential capacity for installing offshore wind farms in Great Lakes is discussed based on the wind pattern and speed. Also, it includes the barriers, issues, wind vision, advantages and disadvantages, the most appropriate locations for erecting the offshore wind farms in Great Lakes, updated offshore wind farms, and statistics for decision-makers, interested communities and investors. This paper is among the rare works that have been done in aspect of statistical and data for the wind offshore in Great Lakes as the moratorium in Canadian side and the difficulties in obtaining permissions in the American side put the offshore wind sector on pause for a long time, and recently (since 2016) it started to get some momentum.
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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 it