A metrics‐based analysis of seasonal daily precipitation and near‐surface temperature within seven Coordinated Regional Climate Downscaling Experiment domains
Why this work is in the frame
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Bibliographic record
Abstract
We compare ensemble mean daily precipitation and near‐surface temperatures from regional climate model simulations over seven Coordinated Regional Climate Downscaling Experiment domains for the winter and summer seasons. We use Taylor diagrams to show the domain‐wide pattern similarity between the model ensemble and the observational data sets. We use the Climatic Research Unit (CRU) and the University of Delaware gridded observations and ERA‐Interim reanalysis data as an additional observationally based estimate of historical climatology. Taylor diagrams determine the relative skill of the seven sets of simulations and quantify these results in terms of center pattern root‐mean square error and correlation coefficient. Results suggest that there is good agreement between the models and the CRU, in terms of their respective seasonal cycles, as shown in Taylor diagrams and bias plots. There is also good agreement between both gridded observation sets. In addition, downscaled ERA‐Interim precipitation is closer to observations than raw ERA‐Interim precipitation. Domains located in the low latitudes and those having high topography appear to have larger biases, especially precipitation.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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