Puget Sound federal task force: federal coordination and collaboration to protect and restore Puget Sound shorelines
Bibliographic record
Abstract
It is well recognized by scientists and natural resource agencies, that restoration and protection of Puget Sound marine shorelines, will help move the needle toward Puget Sound recovery and the multitude of species that rely on nearshore and estuarine habitat. Under the Nearshore and Estuaries section of the Action Plan, federal agency workgroups have been formed to evaluate approaches for improving marine nearshore regulatory and restoration/protection processes, which were identified as a priority early on. The involvement of the Federal Task Force has enabled the active participation of relevant staff to motivate and reach toward beneficial, achievable outcomes. Since some of the actions in the section could not be realized without involvement by state and tribal input, multi-level government approaches have been developed, and these partnerships continue to be enhanced. Coordination and sharing of shoreline protection mechanisms with our Canadian partners could further innovation and increase more consistent education and outreach on both sides of the border. Some of the key actions in the section and specifics of the workgroups’ progress will be presented in this talk.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.026 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.012 | 0.002 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.018 | 0.005 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".