Hydroclimatic Factors of the Recent Record Drop in Laurentian Great Lakes Water Levels
Bibliographic record
Abstract
An extreme low-water supply episode from 1997 to 2000 resulted in the largest 1-yr drop in Lakes Michigan–Huron and Lake Erie water levels (0.92 and 1.03 m, respectively) recorded since measurements began in the early 1800s. Lake Superior water levels were the lowest since 1925. Lakes Erie and Ontario also had relatively low levels. The episode was unusual, particularly when compared to the record-low water episode of the mid-1960s, in that the primary hydroclimatological driver was high air temperatures and not extremely low precipitation. The high air temperatures resulted in unusually high lake evaporation rates and decreased basin runoff. The drop in levels during this episode was compared to other 1–3-yr decreases throughout the period of record. A comparison of the 1997–2000 episode for Lakes Michigan–Huron with the 1960–64 episode, which led to record-low lake levels in 1964, shows that the various elements of the water balance have differing importance in the two episodes.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".