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Record W2069689995 · doi:10.1139/a09-011

Ecosystem consequences of potential range expansions of<i>Orconectes virilis</i>and<i>Orconectes rusticus</i>crayfish in Canada — a review

2009· review· en· W2069689995 on OpenAlexaffvenueabout
Iain D. Phillips, Rolf D. Vinebrooke, Michael A. Turner

Bibliographic record

VenueEnvironmental Reviews · 2009
Typereview
Languageen
FieldEnvironmental Science
TopicCrustacean biology and ecology
Canadian institutionsAlberta Biodiversity Monitoring InstituteGovernment of CanadaUniversity of AlbertaFisheries and Oceans Canada
FundersDirectorate for Biological SciencesU.S. Environmental Protection Agency
KeywordsCrayfishEcologyEcosystemBenthic zoneFreshwater ecosystemInvasive speciesRange (aeronautics)BorealAquatic ecosystemBiologyIntroduced speciesFishery

Abstract

fetched live from OpenAlex

Canadian water bodies are presently experiencing fluctuations in orconectid crayfish ranges largely as a result of human activities. The range of Orconectes virilis , Canada’s most widespread crayfish, is expanding westward into previously uninhabited water bodies of Alberta. This species is also set to re-colonize watersheds in the eastern extent of its range as post-acidification recovery of aquatic ecosystems continues. In addition, the non-native Orconectes rusticus has invaded Central Canada. This species has the potential to rapidly invade boreal water bodies and out-compete native congeners, including O. virilis. Both these crayfish species are known to affect benthic ecosystems and their invasions may have adverse consequences for Canadian water bodies if left unchecked. Here we review the current documented distribution of O. virilis and O. rusticus in Canada, and identify the potential impacts that their invasion may have on boreal aquatic ecosystems. Finally, we consider options that resource managers might consider to contend with these invasions.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.910
Threshold uncertainty score0.179

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.017
GPT teacher head0.243
Teacher spread0.226 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations41
Published2009
Admission routes3
Has abstractyes

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