Bibliographic record
Abstract
Compared to many of the world's contested international watersheds such as the Amu Darya in Central Asia, the Colorado River, or the Nile Basin, the Canadian-United States Great Lakes Basin is a paradox: the level of controversy about the management and use of the waters is inverse to the amount of water in the basin. The lakes themselves contain twenty percent of the world's fresh water). However, comparatively little of this water is currently withdrawn, and only about five percent of that amount is consumed and not returned to the watershed. In 2002, the International Joint Commission (IJC), the Canadian-United States body which administers the 1909 Boundary Waters Treaty, revised its previous consumptive use estimates downward by eighteen percent. Out-of-basin diversions are even smaller. The major transbasin diversion is the Chicago diversion. Chicago and its lakeshore suburbs are authorized by a United States Supreme Court decree to with-draw 3,200 cubic feet per second from Lake Michigan. Only the fact that the Mississippi watershed encompasses most of the metropolitan Chicago area makes this a transbasin diversion. The other major transwatershed diversion, the Long Lake and Ogoki diversions, actually add water to Lake Superior. However, despite the modest levels of present and projected consumptive use and the vast amount of water in the lakes, fears about future in-basin consumptive uses and transbasin diversions have been a major political and legal issue in the basin for more than two decades.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.034 |
| Scholarly communication | 0.014 | 0.019 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.010 | 0.014 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".