Contemporary Issues in Québec’s Temperate Forest — Part 3: Air Pollutants
Bibliographic record
Abstract
This paper is the third in a series documenting contemporary issues in Québec’s temperate forest. It addresses air pollutants, including the acidifying air pollutants that cause acid rain, as well as ground-level ozone and trace elements. It briefly discusses the anthropogenic sources of these pollutants, their current status, their impacts on forest ecosystems and the issues they cause for Québec’s temperate forest. Most air pollutants come from combustion of fossil fuels for energy production or transportation. Since the mid-1990s, thanks to pollutant emission reduction programs implemented in Canada and the United States, emissions and ambient air concentrations of most pollutants have declined significantly. Sugar maple ( Acer saccharum Marsh.), a dominant species in the northern temperate zone, is especially sensitive to air pollutants and their impacts for ecosystems. Previous chronic pollution of these forests has resulted in significant loss of ecosystem services. However, environmental monitoring is ongoing with a view to documenting ecosystem reactions in the wake of contemporary decreases in anthropogenic emissions of air pollutants in North America.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".