Incorporating wind sheltering and sediment heat flux into 1-D models of small boreal lakes: a case study with the Canadian Small Lake Model V2.0
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. Lake models are increasingly being incorporated into global and regional climate and numerical weather prediction systems. Lakes interact with their surroundings through flux exchange at their bottom sediments and with the atmosphere at the surface, and these linkages must be well represented in fully coupled prognostic systems in order to completely elucidate the role of lakes in the climate system. In this study schemes for the inclusion of wind sheltering and sediment heat flux simple enough to be included in any 1-D lake model are presented. Example simulations with the Canadian Small Lake Model show improvements in surface-wind-driven mixing and temperature in summer and a reduction of the bias in the change in heat content under ice compared with a published simulation based on an earlier version of the model.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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