Arthropods of Canadian grasslands: a retrospective of a 40-year project of the Biological Survey of Canada
Bibliographic record
Abstract
Abstract The Biological Survey of Canada initiated a project in 1979 to collect and synthesise information on the native arthropod fauna of the vanishing grassland habitats of Canada. At that time, it was thought that the Canadian arthropod fauna might comprise about 66 000 species. Recent studies suggest that the fauna may exceed 100 000 species, of which >25% may occur in the Prairies Ecozone. Results of this near 40-year project have been published in four volumes of the Arthropods of Canadian Grasslands monograph series of the Biological Survey of Canada. Here, the editors of this series review the grasslands project of the Biological Survey of Canada, summarise the contents of the volumes, and discuss current knowledge on the diversity of the grasslands arthropods of Canada. Whereas information on the species richness of some groups in the Prairies Ecozone is largely complete, information on the diversity of many other groups remains sparse. Reviewing the steps between initiation and publication of the Arthropods of Canadian Grasslands series may aid development of similar projects elsewhere. Identifying knowledge gaps will direct future research efforts. Identifying the diversity of grassland arthropods, their distribution and abundance, and the ecosystem services that they provide will facilitate efforts to conserve the remaining grassland habitats in Canada.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.013 | 0.016 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".