Toward an atlas of Salish Sea biodiversity: the flora and fauna of Galiano Island, British Columbia, Canada. Part I. Marine zoology
Bibliographic record
Abstract
Background: Based on records dating from 1859 to 2021, we provide an overview of the marine animal diversity reported for Galiano Island, British Columbia, Canada. More than 650 taxa are represented by 20,000 species occurrence records in this curated dataset, which includes dive records documented through the Pacific Marine Life Surveys, museum voucher specimens, ecological data and crowd-sourced observations from the BC Cetacean Sightings Network and iNaturalist. New information: We describe Galiano Island's marine animal diversity in relation to the Salish Sea's overall biodiversity and quantify the proportional contributions of different types of sampling effort to our current local knowledge. Overviews are provided for each taxonomic group in a format intended to be accessible to amateur naturalists interested in furthering research into the region's marine biodiversity. In summary, we find that the Pacific Marine Life Surveys, a regional community science diving initiative, account for 60% of novel records reported for Galiano Island. Voucher specimens account for 19% and crowd-sourced biodiversity data 18% of novel records, respectively, with the remaining 3% of reports coming from other sources. These findings shed light on the complementarity of different types of sampling effort and demonstrate the potential for community science to contribute to the global biodiversity research community. We present a biodiversity informatics framework that is designed to enable these practices by supporting collaboration among researchers and communities in the collection, curation and dissemination of biodiversity data.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.016 | 0.028 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".