Checklists of the Hymenoptera of Canada, Alaska and Greenland – Introduction
Bibliographic record
Abstract
The distribution of described, extant species of the insect order Hymenoptera recorded from northern North America will be published in a series of ten checklists. In total, 9250 species in 27 superfamilies and 84 families are recorded from Canada, the state of Alaska (USA) and Greenland (Denmark). Within northern North America, 8933 species are recorded in Canada (96.6% of the total species), Alaska has 1513 (16.4%) and Greenland has 205 (2.2%). Within Canada, Ontario is the province with the most species recorded (5322, 57.5% of all species in northern North America), followed by Quebec (4207, 45.5%) and British Columbia (4063, 43.9%). At the family level, Ontario has 82 of the 84 recorded families, Quebec has 76 and British Columbia has 71. The most species-rich superfamilies in northern North America are Ichneumonoidea (4438 species, 48.0% of the total); Apoidea (1438, 15.5%) and Chalcidoidea (1246, 13.5%). The largest families are Ichneumonidae (3201 species, 34.6% of the total), Braconidae (1237, 13.4%), Tenthredinidae (573, 6.2%), Eulophidae (379, 4.1%) and Pteromalidae (309, 3.3%). Overall species richness of the Hymenoptera in northern North America is compared with surveys in Russia, Germany, Finland and the British Isles.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 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".