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 preliminary descriptive study describes the temporal and spatial distribution of US waterborne disease outbreaks using a geographic information system approach in relationship to rainfall. Regional climate change and variability and their effect on water resources have not been the subject of much study. Climate predictions suggest that storms will be of greater intensity and that the average precipitation event is likely to be heavier. Rainfall and runoff have been associated with individual outbreaks of waterborne disease caused by fecal‐oral pathogens. Waterborne disease outbreak data from 1971 through 1994 were analyzed for groundwater and surface water in 2,105 US watersheds. Between 20 and 40 percent of outbreaks were associated with extreme precipitation. This relationship with extreme precipitation was found to be statistically significant for both surface water and groundwater, although it was more apparent with surface water outbreaks. The authors offer recommendations for improving the assessment of changes in water quality and the effect that climate variability and environmental factors have on waterborne disease risk.
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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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