Extreme Precipitation Events in Chile
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
Extreme precipitation has not only detrimental effects on ecosystems and social and economic sectors, but it is a natural hazard that can trigger floods or soil erosion. This study tries to analyze the extreme rainfalls on different geomorphological units and geographical regions of Chile. For this, data from 87 meteorological stations latitudinally and altitudinally distributed and covering a long period (1980–2018) were used. Results showed that precipitation concentration displays an exponential curve where 30% of the rainiest days were concentrated in only 10% of days with precipitation, proving high irregularity. The decisive weight on annual precipitation falls on a few rainy days with very high rainfall amounts. For return periods > 100 years, extreme events of daily precipitation could reach 109 mm and 305 mm in Northern and Southern Andes Mountains, respectively, while in Northern and Southern Central Depression, their values could be 70 mm and 170 mm, respectively.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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