Forest dynamics in heavily polluted regions. Report No. 1 of the IUFRO Task Force on Environmental Change.
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
<title>Abstract</title> This book is the first volume in a new book series covering many areas of forestry research, published by CABI in association with IUFRO (International Union of Forestry Research Organizations), and also the first report from the IUFRO Task Force on Environmental Change. The book provides a state-of the-art assessment of the extent of air pollution impacts in heavily polluted regions, with case studies from Europe, North America and Russia. It includes a summary for policy makers, and is of interest to researchers and students of forestry, environmental science and pollution studies. The book is arranged in 13 chapters - the first is an introduction, the second provides background information on different types of air pollution and describes the main types of pollutants found in heavily industrialized regions, chapters 3-10 are case studies (3-6 from Russia, 7 from Ontario (Canada), 8 from central and eastern Europe, 9 from California (USA), 10 from the Mediterranean Region), chapter 11 provides an overview of some of the approaches that have been adopted to ameliorate the effects of air pollution in boreal and temperate forests, chapter 12 discusses international activities to reduce pollution at the regional scale, and the last chapter is the summary for policy makers. A subject index is included.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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