Utilization of hydro sources in Canada for green hydrogen fuel production
Bibliographic record
Abstract
The present study comprehensively examines the application of hydro, wave, tidal, undersea current and geothermal energy sources of Canada for green hydrogen fuel production. The estimated potential capacity of each province is derived from official data and acceptable assumptions and is subject to discussion and evaluation in the context of a viable hydrogen economy. According to the findings, the potential for green hydrogen generation in Canada is projected to be 48.86 megatons. The economic value of the produced green hydrogen results in an equivalent of 21.30 billion US$. The top three provinces with the highest green hydrogen production potential using hydro resources, including hydro, wave, tidal, undersea current and geothermal, are Alberta, Quebec, and British Columbia with 26.13 Mt, 7.34 Mt, and 4.39 Mt, respectively. Quebec is ranked first by only considering the marine sources, including 4.14 Mt with hydro, 1.46 Mt with wave, 0.27 Mt underwater current, and 1.45 Mt with tidal, respectively. Alberta is listed as the province with the highest capacity for hydrogen production from geothermal energy, amounting up to 26.09 Mt. The primary objective is to provide comprehensive hydrogen maps for each province in Canada, which will be based on the identified renewable energy potential and the utilization of electrolysers. This may further be examined within the framework of the prevailing policies implemented by local communities and officials in order to develop a sustainable energy plan for the nation.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".