Global forest products trade model.
Bibliographic record
Abstract
<title>Abstract</title> This chapter introduces the Global Forest Products Model (GFPM). The general model structure and the mathematical formulation of the GFPM are provided and key differences and similarities to the modeling approaches developed in the previous chapters are highlighted. The usefulness of the GFPM as a forest sector tool for policy analysis is illustrated by summarizing its applications in a wide array of past and ongoing studies. These studies are summarized under four representative groups: (i) forest sector outlook studies; (ii) studies evaluating the consequences of tariff and non-tariff barriers on the international trade of forest products; (iii) studies projecting the impacts of climate change and forest-based climate change mitigation strategies on forests and forest industries; and (iv) other studies dealing with other important questions, such as the effects of the rise in global planted forest area, illegal harvests, and invasive species. Some of the limitations of GFPM, ways to mitigate these limitations, and its overall usefulness as a forest sector policy analysis tool are also examined.
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 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.004 |
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; both teacher heads agree on what is shown here.
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".