Tracking climate change as a stress multiplier within vulnerable regions of British Columbia’s inner coastal ocean using a multi-platform approach
Bibliographic record
Abstract
Climate change acts as a stress multiplier by enhancing the magnitude of environmental stressors and driving their co-occurrence. These manifestations can devastate marine ecosystems, yet we are deficient in our ability to monitor their emergence and understand their impacts. We utilize an approach that combines innovative ocean observing technologies with traditional ship-based sampling in order to provide integrated, highly-resolved and actionable oceanographic information on multi-stressors within vulnerable regions of the British Columbia (BC) coastal ocean, including the central BC coast, the northern Strait of Georgia, and Bute Inlet. This approach includes the maintenance of the only two Moored Autonomous pCO2 (MApCO2) moorings in Canada, support for Canadian-Pacific Robotic Ocean Observing Facility (C-PROOF) gliders, and deployments of Wirewalker moorings capable of 100s of vertical profiles in a day. These cutting-edge and low-carbon technologies provide high-quality information on ocean conditions autonomously and at resolutions not typically observed with ship-based sampling. The deployment of these technologies will overlap with ship-based sampling that continues multiple >10-year time series targeting biogeochemistry and ecosystem dynamics in order to evaluate against baseline conditions and advance our understanding of impacts from marine stressors. This observational approach collects ocean data for visualization in web-based applications, making information rapidly actionable.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".