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Record W4415163412 · doi:10.1139/cjfas-2025-0045

Canadian freshwater mussels and their host associations

2025· article· en· W4415163412 on OpenAlexaffvenueabout
Benjamin Aubrey, Sarah Elizabeth Steele, André L. Martel, Steven J. Cooke, Katriina L. Ilves

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Invertebrate Ecology and Behavior
Canadian institutionsCarleton UniversityCanadian Museum of Nature
Fundersnot available
KeywordsHost (biology)Context (archaeology)JuvenileLarvaMetamorphosisFish <Actinopterygii>Aquatic animal

Abstract

fetched live from OpenAlex

Freshwater mussels (order Unionida) are one of the world’s most imperiled taxonomic groups of animals. The two families that occur in Canada (Margaritiferidae, Unionidae) produce parasitic larvae (glochidia) that generally rely on attachment to a suitable host fish to facilitate metamorphosis into the juvenile phase. This review synthesizes the current knowledge on the hosts of all 55 species of freshwater mussels in Canada, compiled from 265 citations, 71 of which were newly identified by this review. As of October 2023, evidence for 850 mussel–host associations have been documented, though a relatively small proportion of the evidence was collected in Canada. The winged floater and the lake floater currently have no known hosts, with 14 other species having only a single associated evidence type. This review provides an updated library of current knowledge on hosts of Canadian unionoids, discusses notable trends, and outlines outstanding knowledge gaps to be addressed in future studies. Considering many of the host associations were not studied in Canadian waters, knowledge gaps remain regarding relevant ecological and climatic context in Canada.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.157
Threshold uncertainty score0.316

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.012
GPT teacher head0.208
Teacher spread0.196 · 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 source (direct Gemma or distilled Codex), 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 routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic Sciences→Same topicAquatic Invertebrate Ecology and Behavior→French-language works237,207→