Working Together: How Citizens can help prepare for the consequences of an oil spill
Bibliographic record
Abstract
Geographically situated in the heart of the Salish Sea, San Juan County is at the crossroads of shipping, from both Canada and the United States. Vessel traffic is expected to increase exponentially over the next few years as shipping, especially of fossil fuels, carries products from interior production sites to overseas markets. In light of this, the Action Agenda for San Juan County includes “major oil spills” as one of the three issues to address. As guided by the Marine Resources Committee, our approach is to be inclusive, comprehensive, and pro-active. In this panel, we bring together experts who are “on the ground” working to ensure that data, planning, and actions are coordinated among agencies, concurrent with efforts to train and include citizen volunteers in all phases of the work. Panel:• Marta C. Branch--San Juan County Marine Programs Coordinator (session organizer); Speakers: • Joanruth Bauman --SJC Derelict Vessel program: Catching the problem before it starts • Brendan Cowan –Director, San Juan County Department of Emergency Management Spills-- 101: How Local Marine Managers Can Prepare for Their Role in a Major Spill Response• Dr. Barbara Bentley--SJC MRC Chair—Creating Citizen Scientists• Dan Doty WDFW/DOE— Using the data from pre-spill studies • Dr. Ken Sebens--SJC MRC member—The San Juan County Marine Specimen Bank
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.
How this classification was reachedexpand
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 | 0.001 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".