A Preliminary Assessment of Montreal Process Indicators of Air Pollution for the United States. Environmental Monitoring and Assessment
Bibliographic record
Abstract
Abstract. Air pollutants pose a risk to forest health and vitality in the United States. Here we present the major findings from a national scale air pollution assessment that is part of the United States ’ 2003 Report on Sustainable Forests. We examine trends and the percent forest subjected to specific levels of ozone and wet deposition of sulfate, nitrate, and ammonium. Results are reported by Resource Planning Act (RPA) reporting region and integrated by forest type using multivariate clustering. Estimates of sulfate deposition for forested areas had decreasing trends (1994–2000) across RPA regions that were statistically significant for North and South RPA regions. Nitrate deposition rates were relatively constant for the 1994 to 2000 period, but the South RPA region had a statistically decreasing trend. The North and South RPA regions experienced the highest ammonium deposition rates and showed slightly decreasing trends. Ozone concentrations were highest in portions of the Pacific Coast RPA region and relatively high across much of the South RPA region. Both the South and Rocky Mountain RPA regions had an increasing trend in ozone exposure. Ozone-induced foliar injury to sensitive species was recorded in all regions except for the Rocky Mountain region. The multivariate analysis showed that the oak-hickory and loblolly-shortleaf pine forest types were generally exposed to more air pollution than other forest types, and the redwood, western white pine,
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".