Conferencia bienal de Ecología de Paisaje de IUFRO / Biennial IUFRO Landscape Ecology Conference
Bibliographic record
Abstract
The recent Biennial Conference of the IUFRO Landscape Ecology Working Party 8.01.02, entitled, Sustaining humans and forests in changing landscapes: forest, society and global was held in Concepcion, Chile from the 2nd to the 12th of November, 2012. This Working Party is coordinated by Jiquan Chen (University of Toledo, Ohio, USA) and seeks to promote and facilitate the application of landscape ecology concepts in the policies and practices of forested landscapes worldwide. It also encourages communication and interaction among scientists who have an interest in landscape ecology and forestry. For this purpose, the Working Party has gathered in seven places across the world: Slovenia, the United States, Canada, Japan, Italy, China and two years ago, Portugal. This year, it was the first time that the Working Party gathered further south in the southern hemisphere, and in particular, in Latin America. The region offers new challenges to forest landscape ecology due to its tremendous heterogeneity of ecosystems and diverse socioeconomic conditions. South American forests represent a large fraction of the world's biodiversity and, in turn, are characterized by progressive deforestation and degradation. During the 2012 Conference, we received diverse types of scientific contributions such as keynote speakers' plenaries, symposia, oral presentations, posters and short manuscripts for publication in an 'ISI' journal. The contributing topics ranged from forest landscape management to studies on spatial patterns and ecological processes including the effects of climate change and landscape planning. These studies were conducted in diverse, contrasting landscapes, from the sub-Antarctic forests in Cape Horn, Chile to the Siberian forests, including landscapes from Brazil to Australia and Turkey. It is our major interest to promptly divulgate these works through publication in an open-access scientific journal that is widely known in Latin America. With this goal, the Issue 33(3) of the Bosque Journal is dedicated to the publication of the short manuscripts accepted by the conference's scientific committee. The scientific committee was formed by Louis Iverson (Chair, USDA Forest Service, USA), Joao Azevedo (Instituto Politecnico de Braganca, Portugal), Jean Paul Metzger (Universidade de Sao Paulo, Brazil), Sandra Luque (IRSTEA, France), Ajith Perera (Ontario Ministry of Natural Resources, Canada), Guillermo Martinez Pastur (Centro Austral de Investigaciones Cientificas, Argentina), Damasa Magcale-Macandog (University of the Philippines Los Banos, Philippine) and Jan Boegart (Universite Libre de Bruxelles, Belgium). The process of publication was coordinated by Laura Nahuelhual (Universidad Austral de Chile), who is a member of the conference's organizing committee.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.116 | 0.022 |
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".