The Influence of Canadian Forest Fires on Pollutant Concentrations in the United States
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
High carbon monoxide (CO) concentrations from uncertain origins occurred episodically in the southeastern United States during the summer of 1995. We show that these episodes were caused by large forest fires in Canada. Over a period of 2 weeks, these natural emissions increased CO concentrations in the southeastern United States as well as along the eastern seaboard, a region with one of the world's highest rates of anthropogenic emissions. Within the forest fire plumes, there were also high concentrations of ozone, volatile organic compounds, and aerosols. These results suggest that the impact of boreal forest fire emissions on air quality in the mid-latitudes of the Northern Hemisphere, where anthropogenic pollutant sources have been considered predominant, needs to be reevaluated.
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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 | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it