Invasive Carp monitoring in Canadian waters of the Laurentian Great Lakes Basin, 2021
Bibliographic record
Abstract
In 2021, Fisheries and Oceans Canada’s Invasive Carp Program continued early detection surveillance for Invasive carps in Canadian waters of the Laurentian Great Lakes. A total of 699 field sites were sampled in 28 waterbodies using seven gear types. A total of 46 044 fishes were caught representing 77 species. Buffalo (Ictiobus spp.) and Common Carp (Cyprinus carpio) were used as Invasive carp surrogate species to assess the effectiveness of gear types. A total of 117 buffalo and 915 Common Carp were caught. Boat electrofishing and trammel nets were the most effective at capturing these surrogate species. An additional 79 field sites were sampled at seven locations for larval fishes and eggs using bongo nets. A total of 25 041 larval fishes were caught. No Grass Carp (Ctenopharyngodon idella) were caught during the 2021 early detection surveillance efforts. Surveillance for Invasive carps will continue in 2022, with an emphasis on the lower Great Lakes where the threat of arrival remains highest.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".