The Seattle Aquarium’s collaborative conservation research programs in the Salish Sea
Bibliographic record
Abstract
The Seattle Aquarium’s formal research program, the Seattle Aquarium Research Center for Conservation and Husbandry (SEARCCH), was launched in 2002 and includes over 14 concurrent research projects ranging from marine mammals and sharks to octopus and seastars. The aquarium has been conducting collaborative research projects on fish, marine mammal and invertebrate population status and health in the Salish Sea for over a decade. The projects highlighted here include sea otter, rockfish, sixgill shark, giant Pacific octopus and seastars. Partners include federal and state government biologists from the United States Fish and Wildlife Service (USFWS), United States Geological Survey (USGS), National Oceanic and Atmospheric Association (NOAA) and Washington Department of Fish and Wildlife (WDFW); university biologists from the University of Washington, California State University Humboldt, University of California at Davis and Cornell University; and accredited non-profit institutions such as Point Defiance Zoo and Aquarium, Vancouver Aquarium, Oregon Coast Aquarium, Aquarium of the Bay and Monterey Bay Aquarium. Each of the projects goals, methods and results will be discussed briefly to highlight the benefit of long term collaborative research.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.002 |
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".