Explaining the Non-significant Changes in Ice-off Date over Six Decades at Lake of Bays and Lake Nipissing, South-Central Ontario
Why this work is in the frame
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Bibliographic record
Abstract
The phenomenon of non-significant trends in ice-off date under a warming climate was quantitatively explained by three efforts: exploring possible driving factors where possible and defining new factors to represent snow conditions, identifying the contributing factors through correlation and trend tests, and evaluating relative contributions through partial Mann-Kendall method. Why the ice-off became only slightly earlier over 62 years at Lake of Bays has been satisfactorily assessed: the increased winter temperature, increased total rain and decreased days of snow on ground acted as three promoting drivers to earlier ice-off date, but their promoting functions were effectively offset by adverse changes in four other factors (snowfall slope, precipitation slope, snowpack slope, and last day of snow). The ice-off date at Lake Nipissing did not have a significant trend over 58 years, although there were five factors contributing to the ice-off decline without sufficient offsetting, suggesting that the ice-off of this lake may not be sensitive, or basically elastic, to the climatic variation stressor. Relative contributions of drivers as calculated helped explain how much they contributed to ice-off trends or how much they offset the influences.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.010 | 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 it