A Canadian precipitation analysis (CaPA) project: Description and preliminary results
Bibliographic record
Abstract
A Canadian Precipitation Analysis (CaPA) project for producing 6 h rainfall accumulations at a resolution of 15 km over North America in real‐time is described. The spatial interpolation technique is based on statistical interpolation using short‐range precipitation forecasts from the Canadian Meteorological Centre's (CMC) regional model as the background field with rain‐gauge measurements from the surface network and radar derived rain rates as observations. A pilot study was undertaken over the province of Québec at a resolution of 10 km using additional rain‐gauge observations from a cooperative network for August 2003. This test period allowed the development of methodologies for an objective estimation of background and observation error statistics and for improving the overall quality of rain‐gauge and radar data. The improved skill of the analysis with respect to the model short‐range forecasts is assessed against radar precipitation. The use of additional rain gauges from the surface cooperative network in Québec significantly increased the quality of the resulting analysis.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".