Hydrological impacts of precipitation extremes in the Huaihe River Basin, China
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Precipitation extremes play a key role in flooding risks over the Huaihe River Basin, which is important to understand their hydrological impacts. Based on observed daily precipitation and streamflow data from 1958 to 2009, eight precipitation indices and three streamflow indices were calculated for the study of hydrological impacts of precipitation extremes. The results indicate that the wet condition intensified in the summer wet season and the drought condition was getting worse in the autumn dry season in the later years of the past 50 years. The river basin had experienced higher heavy rainfall-related flooding risks in summer and more severe drought in autumn in the later of the period. The extreme precipitation events or consecutive heavy rain day events led to the substantial increases in streamflow extremes, which are the main causes of frequent floods in the Huaihe River Basin. The large inter-annual variation of precipitation anomalies in the upper and central Huaihe River Basin are the major contributor for the regional frequent floods and droughts.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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