From Planning to Practice: Re-thinking Ecosystem Conservation, Restoration and Rehabilitation of Quebec's Landscapes for a Sustainable and Resilient Future
Bibliographic record
Abstract
We focus our research on developing the best planning approach to select areas for conservation, restoration or rehabilitation, with the objective of maximizing the provision of ecosystem services to people. Our approach balances the benefits and costs of conservation/restoration plans, and considers inequalities in the access to ecosystem services by different groups of people. In this report, we aim to promote an integration of scientific research with policy development, to improve our capacity to address issues related to the planning and execution of natural ecosystems' conservation, restoration and rehabilitation in Quebec. Our mission is to foster collaborative partnerships between academics, government agencies, and relevant stakeholders and to enhance knowledge sharing and co-development of strategies, focusing on the crucial task of ecosystem conservation, restoration and rehabilitation in Quebec.
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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 | 0.022 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.014 | 0.034 |
| Scholarly communication | 0.020 | 0.009 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".