Annotated checklist of the moths and butterflies (Lepidoptera) of Canada and Alaska
Bibliographic record
Abstract
A definitive species list is the foundation of biodiversity and conservation work. As we deal with massive climatic changes in the Anthropocene, knowing which species make up our diverse ecosystems will be critically important if we wish to protect and restore them.<br>The Lepidoptera, moths and butterflies, are the fourth-largest insect order in terms of global diversity, with approximately 158,000 described species. Here we report the distributions of 5431 species that occur in Canada and Alaska, as well as 53 species that have been reported from the region but not yet verified. Additionally, 19 species are listed as interceptions or unsuccessful introductions, and 52 species are listed as probably occurring in the region.<br>The list is based on records from taxonomic papers, historical regional checklists, and specimen data from collections and online databases. All valid species and their synonyms, and all Nearctic subspecies and synonyms are included, except for butterfly subspecies (and their synonyms) that have never been reported from the region. The list is presented in taxonomic order, with the author, date of description, and original genus provided for each name.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.003 | 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) | 0.057 | 0.014 |
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".