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
This chapter focuses the flood of 1993 and the National Flood Insurance Program (NFIP). The spring and summer of 1993 brought torrential rains to the Midwest, along with record-breaking river crests. By August, the upper Mississippi and its tributaries, including the Missouri River, flooded seventeen thousand square miles in nine states. According to the National Weather Service, the 1993 flood broke records for both intensity and duration throughout Missouri, Minnesota, Iowa, and Illinois. U.S. Geological Survey and the Army Corps of Engineers estimated that the flood caused forty-eight deaths and up to $20 billion in property damage. It also displaced about seventy-four thousand people. Many of the victims were uninsured. Although NFIP had been in place for a quarter century, up to 80 percent of eligible property owners had not taken advantage of the opportunity to protect themselves.
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 | 0.000 | 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 | 0.001 | 0.001 |
| 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