CanAM5.1 with lightning parameterization
Bibliographic record
Abstract
CanESM is a fully coupled Earth System Model, developed at the Canadian Centre for Climate Modelling and Analysis, Climate Research Division, Environment and Climate Change Canada (ECCC). The full CanESM code is located here: The Canadian Earth System Model (CanESM) - v5.1.6 (zenodo.org) and includes all the source code, utilities and scripts used to compile and run CanESM5 and to do diagnostics on ECCC's High Performance Computers (see disclaimer regarding usage below; excludes 3rd party dependencies such as NetCDF). The CanESM code is also made openly available at gitlab.com/cccma/canesm. This zenodo repository is for a research version of the Canadian Atmospheric Model, CanAM5.1, with the addition of an interactive lightning parameterization from Etten-Bohm et al (2021), with paper published in GMD: "A new lightning scheme in Canada's Atmospheric Model, CanAM5.1: Implementation, evaluation, and projections of lightning and fire in future climates" by Cynthia Whaley, Montana Etten-Bohm, Courtney Schumacher, Ayodeji Akingunola, Vivek Arora, Jason Cole, Michael Lazare, David Plummer, Knut von Salzen, and Barbara Winter, https://doi.org/10.5194/gmd-2024-24
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.007 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.033 | 0.009 |
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".