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Record W7130381524 · doi:10.4039/tce.2025.10037

Distribution and diversity of terrestrial isopods (Isopoda: Oniscidea) in Canada, including new records and a species checklist

2025· article· en· W7130381524 on OpenAlexaffabout
Hannah Stormer, E. Holly Pike, H. C. Proctor

Bibliographic record

VenueThe Canadian Entomologist · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSubterranean biodiversity and taxonomy
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsChecklistBycatchBiodiversityDistribution (mathematics)Introduced speciesArthropodSpecies diversityGlobal biodiversitySpecies richness

Abstract

fetched live from OpenAlex

Abstract Terrestrial isopods (Isopoda: Oniscidea), also known as sowbugs or woodlice, are one of the few groups of crustaceans with fully terrestrial members. Sowbugs are readily transported by human activity, with many species having been introduced worldwide. Although nonnative sowbugs have been present in Canada for more than 150 years, the study of sowbugs in Canada has been largely overlooked, especially in the Prairie Provinces. We conducted the first survey of sowbug species in Alberta, with additional collections from British Columbia, Saskatchewan, Ontario, and Newfoundland. We compiled an updated Canadian species checklist of 32 species from 12 families, including seven new species records for Canada since the previous 2001 checklist. Species with older records tend to occupy more provinces than species recorded more recently. Nine sowbug species occur in Alberta: all are nonnative and originate from Europe or Asia. Our collection of Nagurus cristatus (Dollfus, 1899) (Trachelipodidae) from Edmonton represents the first record from Canada. We support our identifications with molecular data (cytochrome c oxidase subunit 1 barcode region). Further surveys of sowbugs in the Prairie Provinces may uncover additional species; we encourage reporting of sowbug bycatch from arthropod surveys and note the utility of community science platforms for conducting sowbug surveys.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.347

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.054
GPT teacher head0.211
Teacher spread0.157 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes2
Has abstractyes

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