Fraser Forum Particulates, Energy Consumption, & Affluence
Bibliographic record
Abstract
were 18 percent lower in 1998 than they were in 1940. True or False? 2. In the US, the coal burned by all industry and electricity-generating plants generates less PM10 emissions than residential wood-burning fireplaces. True or False? by Ross McKitrick Many Canadians are concerned about the quality of the air they breathe, both indoors and out. Certainly everyone should celebrate the dramatic improvements in air quality that have happened since the 1970s. However, as important as clean air is, recent major power failures in North America provide striking reminders of just how valuable is our supply of stable, uninterrupted electricity. Unfortunately, the reliability of our electricity supply, at least in Ontario, seems uncertain at best: the grid already operates at full capacity, the population is growing, and the province is actively courting new businesses that are major power users, such as auto plants. On the supply side, a major nuclear plant remains mothballed, natural gas supplies are dwindling, and suitable sites for hydro dams have all been used up. Fortunately we still have coal to rely on … or do we? Ontario’s new Liberal
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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 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.181 | 0.026 |
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".