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Record W2990237194 · doi:10.1007/s11160-019-09587-7

The future of barriers and trapping methods in the sea lamprey (Petromyzon marinus) control program in the Laurentian Great Lakes

2019· article· en· W2990237194 on OpenAlexaff
Scott Miehls, Paul Sullivan, Michael Twohey, Jessica Barber, Rodney B. McDonald

Bibliographic record

VenueReviews in Fish Biology and Fisheries · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsSault Area Hospital
FundersGreat Lakes Fishery Commission
KeywordsLampreyPetromyzonFisheryBiologyLimitingEcologyEngineering

Abstract

fetched live from OpenAlex

Abstract A major duty of the Great Lakes Fishery Commission (GLFC), created in 1955, was the development a program of eradication or management of sea lamprey populations in the Great Lakes for the protection of the Great Lakes fishery. Beginning in the 1980s the GLFC shifted sea lamprey control to an integrated pest management model seeking to deploy control measures which target multiple life stages. Currently control efforts focus on limiting the area of infestation using barriers to migratory adults and eradication of larvae from streams using selective pesticides. Feedback on program effectiveness is obtained by trapping migratory adult lamprey at a series of index sites around the basin. The GLFC continues to support multiple research initiatives to develop additional control, improve current control measures, and further advance the sea lamprey control program. During the past six decades sea lamprey control in the Great Lakes has evolved as the research program has identified technological advances. Here we summarize the current state and recent advancements for two of the sea lamprey control program’s core elements, barriers and traps, highlight challenges to be addressed to continue the advancement of these program elements, and provide a series of research questions to spur interest within the research community. Further, because considerable information about these program elements is scattered among grey literature and technical reports, we summarize the history of barriers and traps in sea lamprey control in the included appendices to provide relevant program background to anyone interested in pursuing these research topics.

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)0.003
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 score0.417
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.012
GPT teacher head0.280
Teacher spread0.268 · 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

Citations46
Published2019
Admission routes1
Has abstractyes

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