Bibliographic record
Abstract
Heavy rainfall events frequently occur in Kochi Prefecture where is not covered by XRAIN network. Then, we are working to construct our own X-MP radar network in Kochi prefecture and to develop quasi-real time Quantitative Precipitation Estimation (QPE) algorithm. The present study aims to verify the accuracy of QPE derived from 3 X-band MP radars (Asakura, Monobe, and Aki radars) by comparing with the data of rain gauge. We employed R-Kdp relationship for heavy rain which has Zh ≧ 30 and Kdp ≧ 0.3 as a QPE method and R-Z relationship for weak rain. Results showed that our radars underestimated slightly except for Monobe radar which estimates almost same with the data obtained from rain gauge and the correlation between radar data and rain gauge data was about 0.8.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.006 |
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; both teacher heads agree on what is shown here.
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".