Should Canada go nuclear? An analysis of Canada’s small modular reactor strategy to meet 2050 net zero goals
Bibliographic record
Abstract
Like most developed countries, Canada wants to reduce the risks and impacts of climate change.Doing so involves major decarbonization of Canada's energy sector.A major question is how to switch our current energy sector from fossil fuels to clean energy production while meeting energy demand and current employment rates.International organizations such as the Intergovernmental Panel on Climate Change (IPCC) have recommended a large increase in the world's nuclear energy production.A major barrier to constructing conventional nuclear power plants has been the complex regulations and large cost overruns of traditional reactors.Instead, the nuclear industry, and Canada aim to begin constructing Small Modular Reactors (SMR).These will potentially allow the nuclear industry to standardize production, realize scale economies in construction, and lower the regulatory burden.By building the reactor within a factory, companies hope to save time and costs relative to on-site construction.The question this paper addresses is how do we do that in Canada, and how much nuclear energy should we generate to meet our Net-Zero goals by 2050?The recommendation is based on analysis of the current literature and 10 expert interviews.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.011 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".