Taking Fire Science and Practice to the Next Level: Report from the PAGES Global Paleofire Working Group Workshop 2017 in Montreal, Canada – Paleofire Knowledge for Current and Future Ecosystem Management
Bibliographic record
Abstract
This report summarizes the outcome of the PAGES Global Paleofire Working Group workshop 2017 that took place in Montreal, Canada – Paleofire knowledge for current and future ecosystem management. The workshop aimed to (1) discuss the importance of past fire or paleofire research, focused on long-term influence of fire on the environments worldwide, in nature conservation, (2) find ways to integrate scientific achievements of paleofire research into ecosystem management practices, and (3) start the dialogue with ecosystem managers, practitioners and policymakers (EMPPs). With this report, the members of the Global Paleofire Working Group would like to open a discussion about how igniting new collaborations with EMPPs and make paleofire data useful for fire risk management. We recognized four main challenges in communication and cooperation between scientists and EMPPs: little awareness of EMPPs about paleofire research, differences in professional language used in an operational context by scientists and EMPPs, scientific data availability, and costs of paleoecological expertise. Moreover, we indicate the way to improve the communication between scientists and EMPPs by proposing a scheme of cooperation between both groups. We want to encourage researchers working in various fields of paleoecology to open up for the cooperation with EMPPs in the future, especially helping to create ecosystem management plans, because paleoecological data carry important information about the evolution of ecosystems that is vital in the context of global change.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".