The Power of Real Options - Evaluating nuclear energy investments in Ontario
Bibliographic record
Abstract
The Ontario electricity sector is at a critical junction in its history. With decreasing generation\ncapacity and escalating demand, a province-wide shortfall is projected to emerge before the end\nof the decade. The situation has predetermined that capital investments in new installed\ngeneration capacity will have to be made in order to ensure a stable and reliable supply. The\nobjective of this thesis is to evaluate capital investment decisions that will be made in the near\nfuture. We place particular emphasis on nuclear generation, which will continue to play a major\nrole in meeting base load needs. More specifically, we consider decisions to invest in new\nnuclear generation and refurbishment of existing plants. In order to evaluate these investment\ndecisions in a flexible manner, we will employ the real options methodology. The real options\napproach is relevant in the context of strategic energy investment planning due to its superior\nability in dealing with uncertainties and incorporating management’s flexibilities into the\nvaluation process. Our findings confirm that the real options approach uncovers hidden\nstrategic value and provides critical insights to the investment decision making process.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".