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
A traditional ecological knowledge summit The Global Center for Climate Change and Transboundary Waters (GCTW) cohosts a Traditional Ecological Knowledge Summit (1), as Gail Krantzberg (2), Peter Czajkowski, Dawn Martin-Hill, Rohini Patel, Hiliary Monteith, and Drew Gronewold explain. The Global Center for Climate Change and Transboundary Waters (GCTW) integrates hydroclimate modeling, water quality forecasting, and community-engaged mixed methods that harmonize and propagate Traditional Ecological Knowledge (TEK), Indigenous Knowledge (IK), and Western Science (WS) into robust 21st-century transboundary water resources governance protocols. The U.S. National Science Foundation and the Canadian Social Science and Humanities Research Council fund the Center. It supports a multinational network of researchers that is designed to promote information sharing across borders.
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 | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.027 | 0.004 |
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