Oceanographic conditions and harmful algae in the Strait of Georgia, Canada – outcomes of seven years of monitoring with the citizen science program.
Bibliographic record
Abstract
The Pacific Salmon Foundation’s Citizen Science Oceanography Program was started in 2015, with assistance from Fisheries and Oceans Canada (DFO) and Ocean Networks Canada (ONC). The purpose of this innovative program is to obtain high-resolution data on oceanographic conditions and lower trophic levels that can be used to assess conditions relevant to juvenile salmon survival in the Salish Sea. Sampling occurs at 50-80 sites, about 20 times a year from February to October, resulting in ~1500 oceanographic stations each year, which are archived at ONC and the Strait of Georgia Data Centre. Analysis of oceanographic conditions (temperature, salinity, dissolved oxygen, turbidity, and nutrients) and phytoplankton dynamics with emphasis on harmful algae species (e.g. Alexandrium spp., Dinophysis spp., Heterosigma akashiwo, Noctiluca scintillans, and Pseudo-nitzschia spp.) are presented. Other outcomes of this program include contributions to the annual ‘State of the physical, biological and selected fishery resources of Pacific Canadian marine ecosystems’ DFO report and the Oceanographic Atlas of the Strait of Georgia, as well as scientific studies.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".