Bibliographic record
Abstract
To meet forecasted load growth in the Alberta electricity market, various power generation technologies are available. Each has different attributes, benefits and limitations. Wind power generation technology is an attractive option for the reduction of emissions however it also imposes additional costs relative to other technology options. The location, variability and intermittency of wind power generation in the Alberta system create reliability issues (supply always equaling demand in real-time) and efficiency issues that would not exist if no wind capacity was installed. Reliability can be more efficiently attained with less total installed generation and transmission capacity when wind is not in the system. The volatility of output from wind generation also imposes or transfers costs on load and other generators to manage reliability. In order to assess the trade-off between the benefits and costs of wind power generation in Alberta, the effects of wind on the electricity system and the costs it imposes should be analyzed. The effects of various public policies on the results of that analysis will also guide decisions to improve economic efficiency. Comparison of these costs to the benefits of wind as a renewable technology can assist in determining the required willingness to pay for wind as a renewable energy source. Alberta currently has the capacity to generate 939 MW of electricity from wind power, representing approximately 7% of installed capacity. This capacity has come at a cost and reduced market efficiency, as well as affected the objectives of all market participants. It is therefore questionable whether it is efficient to add more wind power capacity to the Alberta electricity grid.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".