Application of the Canadian land surface scheme (class) to the simulation of energy and water fluxes over alpine tundra
Bibliographic record
Abstract
The ability of the Canadian Land Surface Scheme (CLASS) to simulate energy and moisture fluxes over tundra surfaces is tested using three dataseis collected at alpine sites in southern Alberta and British Columbia, Canada. Initial runs of the model indicate that the ground heat flux tends to be overestimated and the latent heat flux underestimated on average. With the incorporation of minor modifications to the surface thermal conductivity, the vegetation rooting depth and the calculation of the surface soil moisture, the mean bias errors in the latent and ground heat fluxes are reduced to more acceptable levels. Despite the fact that the current version of CLASS does not explicitly take into account the effects of spatial heterogeneity at the sites, the model is found to perform reasonably well with these modifications. It is recommended that the next version of CLASS incorporate a mosaic approach which will allow further subdivision of the modelling area, and that a set of algorithms specific to sparse canopies be implemented into the code.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".