Comment on “application of the Canadian regional climate model to the Laurentian Great Lakes region: Implementation of a lake model”
Bibliographic record
Abstract
Abstract A recently published slab model formulation of lake thermodynamics (Goyette et al., 2000), including an empirical factor to adjust the incoming heat flux so that the modelled lake surface temperature agrees with observed climatology, leads to a distinct lack of energy conservation. The empirical adjustment conceptually represents an exchange of heat between the mixed‐layer water (the slab that is explicitly simulated in the model) and deeper layers of water. It ensures a realistic temporal progression of temperature in the mixed layer, but the thermodynamic balance of the deeper water is not considered. When the deeper water is considered, it is found that the empirical adjustment accounts for the entire heat input to the deeper water, and on an annual mean basis, it is considerably unbalanced. This reveals a flaw in this model concept and, although not entirely invalidating the model, it needs to be included as a caveat in its use.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".