Clayoquot Sound Harmful Algal Blooms Investigation of Warn Bay to Tranquil Inlet - 2019
Bibliographic record
Abstract
A large and successful shellfish and fish industry resides in the northeastern Pacific, so when a heat anomaly now known as the "Blob" was discovered in the area there was concern about its impacts. Since many harmful algal blooms (HABs) thrive in higher temperatures, it was important to determine if the "Blob" caused more favorable environmental conditions to support increased amounts of algae in the water. Measurements were taken in 2019 for essential nutrients such as nitrates, phosphates, and silicates, as well as water properties including temperature, salinity, density, dissolved oxygen, transmissivity, and fluorescence. These were then compared to data from 2014 to verify if there was a difference between two years that the "Blob" was confirmed to have appeared. This analysis focused on a transect from Warn Bay to Tranquil Inlet in Clayoquot Sound, British Columbia, Canada. In 2019, the comparison showed a decrease in nutrients at the water's surface despite consistent values at the sea floor, as well as an increase in temperature that correlated with a decrease in transmissivity and an increase in fluorescence near the surface. This evidence supported the possibility of increased favorable conditions for HABs with the "Blob" since 2014. If persistent, future years would have to face increased risk of these HABs contaminating seafood supplies.
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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 | 0.002 | 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) | 0.002 | 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".