Mapping a Transboundary Flood from the USA to Canada using Space-Air-Ground Remote Sensing
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
Transboundary flooding caused by unique terrains can result in catastrophic damages across multiple countries and political complications in flooding responses and managements.A severe flooding occurred in mid-November, 2021, in Washington (WA), USA, triggered by intense atmospheric rivers, heavy rainfall, and river outflows.The floodwaters flowed northeast from Washington to British Columbia (BC), Canada, causing massive damages and losses in both regions.These include at least five fatalities, thousands of flooded homes, tens of thousands of evacuated residents, and hundreds of thousands of livestock deaths (Gillett et al. 2022;Watterodt and Doberstein 2023).The huge economic losses made this event one of the most expensive disasters in the history of Canada (CleanBC 2021).
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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