Simulated heat storage in Canada's most northern lake: Towards a 3 dimensional model
Bibliographic record
Abstract
This work focuses on heat fluxes and hydrodynamic of Ward Hunt Lake, Canada's most northern lake, as well as its response to climate variations. The project aims to implement a heat budget model, in order to improve our understanding of underlying mechanisms (water column stability, heat advection from waterflows during melting periods, influence of net solar radiation and air temperature variations, feedback effects). The first step is to build a unidimensionnal model, based on tne model from Vincent et al. (2008) implemented for the perennial-ice-covered Lake A, very close to Ward Hunt Lake. Then the model will be extended to two dimensions, along a vertical transect. Finally, the feasibility of extending it to a 3D model will be explored, in order to determine the entire data needed to do so. The project will be completed by a field campaign on Ward Hunt Island and northern Ellesmere Island, in the Canadian High Arctic, during 3 weeks in July 2017.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".