Climate and hydrologic change across the Great Lakes region and other transboundary waters
Bibliographic record
Abstract
Climate and hydrologic change across the Great Lakes region and other transboundary waters Scott Steinschneider, M. Altaf Arain, Paulin Coulibaly, Andrew Gronewold, and Gail Krantzberg, explore climate and hydrologic change across the Great Lakes region in North America and other transboundary waters. Hydroclimate extremes are transforming water landscapes in transboundary regions. These systems are particularly susceptible to hydroclimatic variability due to shared governance structures, interconnected ecosystems, and a wide range of water users. The Great Lakes basin – one of the world’s largest freshwater systems, shared by Canada, the United States, and numerous Indigenous sovereign nations – exemplifies how shifting hydroclimatic conditions are challenging conventional approaches to water management across borders. In this region, the impacts of these changes are evident in increased flooding, shoreline erosion, economic disruption, ecosystem stress, and rising uncertainty surrounding water availability and quality.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".