Horizon scan of conservation issues for inland waters in Canada
Bibliographic record
Abstract
Horizon scanning is a systematic approach increasingly used to explore emerging trends, issues, opportunities, and threats in conservation. We present the results from one such exercise aimed at identifying emerging issues that could have important scientific, social, technological, and managerial implications for the conservation of inland waters in Canada in the proximate future. We recognized six opportunities and nine challenges, for which we provide research implications and policy options, such that scientists, policy makers, and the Canadian society as a whole can prepare for a potential growth in each of the topic areas we identified. The issues spanned a broad range of topics, from recognizing the opportunities and challenges of community-enabled science and the need to consider the legal rights of nature, to the likely increase of pharmaceuticals in wastewater due to an aging population. These issues represent a first baseline that could help decision makers identify and prioritize efforts while simultaneously stimulate new research avenues. We hope our horizon scan will pave the way for similar exercises related to the conservation of biodiversity in Canada.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.009 | 0.017 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".