Physiological responses coupled with plankton productivity and chemical oceanographic monitoring in a dynamic coastal BC environment.
Bibliographic record
Abstract
Coastal margins are under increasing human-induced pressures including eutrophication and ocean acidification, which interact with natural environmental fluctuations in ways that can exacerbate calcium carbonate (CaCO3) mineral corrosivity. The temporal and spatial patterns of these pressures are in general very under-studied. Ocean acidification negatively impacts a range of species, especially those dependent on CaCO3 saturation states for shell formation like marine shellfish. Marine shellfish are socio-economically important as worldwide aquaculture organisms and bioindicator species, used for generating indicators of coastal health. The capacity for marine populations to adapt to these changes is unknown, and the loss of dominant coastal and estuarine organisms such as shellfish may significantly alter marine ecosystem structure and function, as well as threaten food security. This research combines lower trophic level monitoring (plankton analysis), physiological responses (functional genomics of multiple species of shellfish) and oceanographic monitoring at a field site in the northern Salish Sea in British Columbia (BC), Canada. This initial project is a novel pairing of these technologies in situ, and provides information on coastal variability and impacts on ecosystem productivity in a poorly sampled portion of the BC coastal margin. This work is currently ongoing, but preliminary results of gene expression studies of multiple commercial shellfish species and accompanying plankton work will be discussed. In addition linkages of the biological research to variability of coastal carbonate chemistry will be discussed, with a view to determining the impact of ocean acidification on the long-term health and productivity of coastal ecosystems in BC.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".