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Record W3158065868 · doi:10.24908/iqurcp.9447

21. Invasion of Asian Carp in the Great Lakes

2018· article· en· W3158065868 on OpenAlexvenueno aff
Kassandra Smrekar, Shingo Tanaka, Lavie Williams

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsInvasive speciesCarpIntroduced speciesFisheryHabitatBiodiversityGeographyGovernment (linguistics)Fish <Actinopterygii>EcologyEnvironmental planningBiology

Abstract

fetched live from OpenAlex

A recent threat posed to the Great Lakes and adjoining waterways is the Asian Carp. This large bodied fish originated from Asia and was first imported to the North American between 1960 to 1970. Their migration northward through the Mississippi River eliminated native freshwater species through competition of habitat and food resources. It is imperative to focus on the potential invasion of the Asian Carp because the risk assessment is high that the carp would eliminate all native species. Currently the carp are at the border of entering Lake Michigan, which would then provide access to the rest of the freshwater regions in the surrounding area. Ultimately, the loss of lake biodiversity is the fundamental problem and is coupled with economic issues. Bowfin Environmental Consulting INC and various invasive species awareness programs have been utilized to provide guidance on undertaking a project that involves an aggressive invasive species. The challenge faced will be to determine a method in which to prevent the invasion of Asian Carp. Examining their migration patterns, importation laws of live fish, and the policies of invasive species, will provide insight on the approach that should be taken to eliminate the threat of Asian Carp. It is also important to analyze which native species are most susceptible to becoming extinct. Overall, the intention is not only to increase government, scientific, and public awareness of this issue, but also to provide methods that can be implemented to prevent and eradicate the spread of Asian Carp in North American waterways.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.963
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.084
GPT teacher head0.339
Teacher spread0.254 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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