Preliminary Assessment of Whatcom and Skagit Shellfish Bed Exposure to Fecal Bacteria using the Salish Sea Model
Bibliographic record
Abstract
High levels of fecal bacteria have impacted key commercial and tribal shellfish harvesting at shellfish beds located in Samish Bay, Portage Bay, and Drayton Harbors in the Skagit and Whatcom County regions of the Salish Sea. Despite extensive pollution prevention and source control efforts since the 1990s, the problem of shellfish bed exposure to fecal bacteria persists. Based on site-specific experience, practitioners identified the need to better understand the marine circulation of pathogens near shellfish beds. Specifically, how currents driven by tides and winds move freshwater from rivers, streams, and outfalls is not well understood at these locations. The hypothesis is that major loading of the pathogens to critical shellfish habitats occurs through freshwater streams, causing direct exposure to fecal bacteria in the nearshore intertidal brackish environment. Improved understanding of circulation, mixing, and transport would provide the necessary insight to implement corrective actions. In this talk, we present preliminary results from the first two-quarters of a two-year project to conduct a detailed analysis of the freshwater plume(s) circulation and transport at these bays with shellfish beds. In addition to direct transport (hydrodynamics and circulation), the study seeks to improve our understanding of persistent levels of fecal bacteria. This would be accomplished by implementing a fecal bacteria module for the Salish Sea Model with application to Skagit and Whatcom County study areas, resulting in improved understanding of freshwater plumes dynamics and transport. Assessment of exposure of growing areas to freshwater plumes, considering their frequency and duration, is presented. The Salish Sea Model is a transboundary model; plumes from Georgia Strait will be included- especially for Drayton Harbor, which is located at the US/Canada border. Tribal, state, and local water quality programs are important partners on this work, and the results will benefit tribal, commercial, and recreational shellfish harvesters.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 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".