Going off the deep end: Using public outdoor swimming pools as a detection survey tool for invasive insects
Bibliographic record
Abstract
In 2017, the Canadian Food Inspection Agency analyzed the contents of outdoor swimming pool filters in Essex County to determine if pools could be used to detect invasive insects. Insects from two orders and nine families were collected, with Scarabaeidae (Coleoptera) being the most numerous taxon. In addition to Japanese beetle (Popillia japonica Newman), we caught scooped scarab (Onthophagus hecate (Panzer)), European chafer (Amphimallon majale (Razoumowsky)), Asiatic garden beetle (Maladera castanea (Arrow)), northern masked chafer (Cyclocephala borealis Arrow) and southern masked chafer (C. lurida Bland) in the filters. Of these, M. castanea is a new record for Ontario, while C. borealis is a new Canadian record. In total, 74 scarab beetles were captured in the filters and all of them were in good condition to allow for morphological identification. These results show that examining the contents of pool filters shows promise as a detection tool for non-indigenous insects.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".