Finding a PATH toward Scientific Collaboration: Insights from the Columbia River Basin
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
"Observed declines in the Snake River basin salmon stocks, listed under the U.S. Endangered Species Act (ESA), have been attributed to multiple causes: the hydrosystem, hatcheries, habitat, harvest, and ocean climate. Conflicting and competing analyses by different agencies led the National Marine Fisheries Service (NMFS) in 1995 to create the Plan for Analyzing and Testing Hypotheses (PATH), a collaborative interagency analytical process. PATH included about 30 fisheries scientists from a dozen agencies, as well as independent participating scientists and a technical facilitation team. PATH had some successes and some failures in meeting its objectives. Some key lessons learned from these successes and failures were to: (1) build trust through independent technical facilitation and multiple levels of peer review (agency scientists, independent participating scientists and an external Scientific Review Panel); (2) clarify critical uncertainties by developing common data sets, detailed sensitivity analyses, and thorough retrospective analyses of the weight of evidence for key alternative hypotheses; (3) clarify advice to decision makers by using an integrated life cycle model and decision analysis framework to evaluate the robustness of potential recovery actions under alternative states of nature; (4) involve key senior scientists with access to decision makers; (5) work closely with policy makers to clearly communicate analyses in nontechnical terms and provide input into the creation of management alternatives; and (6) recognize the trade-off between collaboration and timely completion of assignments."
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.011 |
| Open science | 0.002 | 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