Long-term monitoring of macroalgal biodiversity in Stanley Park, Vancouver, British Columbia
Bibliographic record
Abstract
The sampling was started by Varoon P. Supratya and Siobhan Schenk. Starting in September 2025, Evan Kohn, who has been very involved with the transects since 2023, is now co-leading the project. Macroalgae are marine foundation species in intertidal ecosystems, but data regarding their historical abundance, diversity, and phenology remains lacking in many regions, including British Columbia. This absence of historical baselines may hinder assessments of how macroalgae are affected by anthropogenic stressors, such as extreme weather events (e.g., 2021 heat dome) or invasive species. Obtaining baseline data may be especially important for urban intertidal zones, where the impact of increasing anthropogenic stressors is underappreciated. To fill this data gap, they started a collaborative long-term survey in 2021 to document year-round macroalgal biodiversity in a highly biodiverse urban intertidal zone around the Girl in a Wetsuit Statue in Stanley Park, Vancouver, British Columbia, Canada (49.30275394688415, -123.12643462372476). For easy data visualization, the Shiny app linked here may be useful, but we strongly recommend doing your own data analysis. Please cite the Borealis dataset and/or the associated publication, not the Shiny app.
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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 | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".