The response and role of ice cover in lake-climate interactions
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
This paper reviews the current state of knowledge pertaining to the interactions of lake ice and climate. Lake ice has been shown to be sensitive to climate variability through observations and modelling, and both long-term and short-term trends have been identified from ice records. Ice phenology trends have typically been associated with variations in air temperatures while ice thickness trends tend to be associated more to changes in snow cover. The role of ice cover in the regional climate is less documented and with longer ice-free seasons possible as a result of changing climate conditions, especially at higher latitudes, the effects of lakes on their surrounding climate (such as increased evaporation, lake-effect snow and thermal moderation of surrounding areas, for example) can be expected to become more prominent. The inclusion of lakes and lake ice in climate modelling is an area of increased attention in recent studies. An important step in improving predictions of ice conditions in models is the assimilation of remote sensing data in areas where in-situ data is lacking, or non-representative of the lake conditions. The ability to accurately represent ice cover on lakes will be an important step in the improvement of global circulation models, regional climate models and numerical weather forecasting.
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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) | 0.000 | 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