Classification of Annual Great Lakes Ice Cycles: Winters of 1973–2002*
Bibliographic record
Abstract
Abstract Annual seasonal average ice cover from 1973 to 2002 and associated dates of first ice, last ice, and ice duration are presented and discussed. The annual seasonal average ice cover of each Great Lake is used to define three ice cycle classes: mild, typical, and severe. About half of the severe ice cycles occurred from 1977 to 1982 and about half of the mild ice cycles occurred from 1998 to 2002. The seasonal progression of daily lake-averaged ice cover, spatial differences in ice cover, and differences among the Great Lakes for mild, typical, and severe ice cycles are discussed within the context of lake bathymetry and winter air temperatures. Seasonal average ice cover is larger on Lakes Superior, Erie, and Huron relative to Lakes Michigan and Ontario, because of shallower depths (for Erie and Huron) and lower air temperatures (for Superior) relative to Lakes Michigan and Ontario. This ice cycle classification scheme can be used to compare future Great Lakes ice cycle severity with this 30-winter benchmark.
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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 | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| 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 | 0.001 |
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".