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
In many parts of the world, forests provide high quality water for domestic, agricultural, industrial, and ecological needs, with water supplies in those regions inextricably linked to forest health. Wildfires have the potential to have devastating effects on aquatic ecosystems and community drinking water supply through impacts on water quantity and quality. In recent decades, a combination of fuel load accumulation, climate change, extensive droughts, and increased human presence in forests have resulted in increases in area burned and wildfire severity-a trend predicted to continue. Thus, the implications of wildfire for many downstream water uses are increasingly concerning, particularly the provision of safe drinking water, which may require additional treatment infrastructure and increased operations and maintenance costs in communities downstream of impacted landscapes. A better understanding of the effects of wildfire on water is needed to develop effective adaptation and mitigation strategies to protect globally critical water supplies originating in forested environments.
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 | 0.001 | 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 | 0.009 |
| 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