Student Independent Projects Sustainable resource Management 2015: Public Perception of Hydroelectric Power and the Suitability of Small-Scale Generation as an Alternate Power Source in Newfoundland and Labrador
Bibliographic record
Abstract
Hydroelectricity started with the wooden waterwheel and various types of waterwheels have been used in Europe and China for approximately 2000 years (Paish, 2002). The technique to use water to generate electricity was nearly perfected during the Industrial Revolution with efficiencies approaching 70% in many thousands of waterwheels in use (Paish, 2002). Improved engineering skills in the 19th century led to the development of modern-day turbines. The first hydro-turbine was created in France in the 1820s and this led to many waterwheels being replaced by turbines, as many people were thinking of how to exploit hydropower for large-scale generation of electricity (Paish, 2002). The golden age of hydropower was during the first half of the 20th century before oil became the main source of energy for most of the modern world. The development of hydropower in the 20th century was usually associated with the building of large dams. These dams while providing a major reliable power source and flood control benefits, flooded large areas of fertile land and displaced many thousands of inhabitants in the surrounding areas (Paish, 2002
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".