The spiders of Prince Edward Island: experts and citizen scientists collaborate for faunistics
Bibliographic record
Abstract
Although lists of spider species have been compiled for all of Canada’s provinces and territories, the spider fauna of Prince Edward Island (PEI) is poorly known. Based on the efforts of citizen scientists, naturalists, and scientists on PEI and researchers at the Centre for Biodiversity Genomics, we present the first comprehensive list of spider species on the island, increasing the known number from 44 to 198. The Centre for Biodiversity Genomics conducted intensive collection in Prince Edward Island National Park; Nature PEI citizen scientists and naturalists contributed specimens from across the island from several different habitats. This provincial list is dominated by the araneoid families, Linyphiidae, Theridiidae, and Araneidae, with 55, 27, and 22 species, respectively. Several non-native species, such as the theridiid Eurasian False Black Widow Spider (Steatoda bipunctata (L.)) and the araneid Red-sided Sector Spider (Zygiella atrica (C.L. Koch)), have been collected in several locations on the island, suggesting that they are well established. This work highlights the effectiveness of collaboration among citizen scientists, naturalists, and professional researchers to further our knowledge of species diversity and distributions.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".