The Changing Face of Winter: Lessons and Questions From the Laurentian Great Lakes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Among its many impacts, climate warming is leading to increasing winter air temperatures, decreasing ice cover extent, and changing winter precipitation patterns over the Laurentian Great Lakes and their watershed. Understanding and predicting the consequences of these changes is impeded by a shortage of winter‐period studies on most aspects of Great Lake limnology. In this review, we summarize what is known about the Great Lakes during their 3–6 months of winter and identify key open questions about the physics, chemistry, and biology of the Laurentian Great Lakes and other large, seasonally frozen lakes. Existing studies show that winter conditions have important effects on physical, biogeochemical, and biological processes, not only during winter but in subsequent seasons as well. Ice cover, the extent of which fluctuates dramatically among years and the five lakes, emerges as a key variable that controls many aspects of the functioning of the Great Lakes ecosystem. Studies on the properties and formation of Great Lakes ice, its effect on vertical and horizontal mixing, light conditions, and biota, along with winter measurements of fundamental state and rate parameters in the lakes and their watersheds are needed to close the winter knowledge gap. Overcoming the formidable logistical challenges of winter research on these large and dynamic ecosystems may require investment in new, specialized research infrastructure. Perhaps more importantly, it will demand broader recognition of the value of such work and collaboration between physicists, geochemists, and biologists working on the world's seasonally freezing lakes and seas.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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