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Invasive Aquatic Species in Ontario

2005· article· en· W1986851856 on OpenAlexfundaboutno aff
Steven Kerr, Christopher S. Brousseau, Mark Muschett

Bibliographic record

VenueFisheries · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Ecology and Invasive Species
Canadian institutionsnot available
FundersMinistry of Natural Resources
KeywordsLegislationAquacultureFisheryInvasive speciesBusinessRecreationStockingOrnamental plantFish <Actinopterygii>Aquatic environmentAquatic animalAquatic ecosystemAquatic plantEnvironmental planningEnvironmental protectionEcologyBiologyGeography

Abstract

fetched live from OpenAlex

We review eight different pathways for invasion by aquatic species into Ontario. These include fish stocking programs, private aquaculture, bait industry, aquarium and ornamental pond industry, live food fish industry, recreational boating, canals and diversions, and commercial shipping. These pathways have been responsible for the introduction of more than 160 invasive aquatic organisms into Ontario. Due to several gaps in policy and legislation, we conclude that the greatest potential pathways for the future introduction and spread of invasive aquatic species are associated with ballast water from the shipping industry, the live food fish industry, and the ornamental pond/aquarium trade. We offer recommendations to reduce the potential for establishment of additional invasive aquatic species. New legislation is required and public awareness programs need to be expanded. Response protocols need to be developed which clearly define roles and responsibilities of different agencies. Finally, a more coordinated effort between stakeholders and various levels of government with regard to invasive aquatic species is needed.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.047
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.017
GPT teacher head0.182
Teacher spread0.166 · 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

Citations48
Published2005
Admission routes2
Has abstractyes

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