An assessment of long-term trends in hydrologic components and implications for water levels in Lake Superior
Bibliographic record
Abstract
The combination of climate change and natural periodicities in meteorological variables are demonstrating significant impacts on the water resources of Lake Superior within the Laurentian Great Lakes system of North America. Statistical analyses of long-term records are used to demonstrate how changes over time may be interpreted very differently, depending upon the timeframe over which the analyses are made. Non-linear regression modelling shows that, while increasing trends in overland and overlake precipitation, flows and runoff occurred during the first decades of the twentieth century, very different trends are apparent for the period 1970–2005. For this latter period, increasing rates of air overlake temperature and lake evaporation are occurring but all other parameters are demonstrating decreasing trends. The result is a decline in water levels in Lake Superior at the rate of approximately 1 cm per year over the last 35 years. The results are used to show that to avoid decreasing water levels in Lake Superior, the discharge through St Mary's River must be decreased to approximately one-half the long-term annual average, the results of which will have dramatic implications for ships' cargo levels and hydroelectric energy generation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".