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Record W6991341146

Genetic and phenotypic population structure of invasive sea lamprey, Petromyzon marinus, in the Laurentian Great Lakes and Finger Lakes

2021· dissertation· en· W6991341146 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2021
Typedissertation
Languageen
FieldBusiness, Management and Accounting
TopicDigital Innovation in Industries
Canadian institutionsnot available
Fundersnot available
KeywordsPetromyzonLampreySalvelinusPopulationGenetic structurePhilopatryLake sturgeonmtDNA control region
DOInot available

Abstract

fetched live from OpenAlex

Sea lamprey, Petromyzon marinus, are an invasive species in the Laurentian Great Lakes and Finger Lakes. The parasitic feeding stage is particularly damaging to the lakes’ ecosystem as sea lamprey wound and kill environmentally and economically important fish such as lake trout, Salvelinus namaycush. Since the sea lamprey invasion in the late 1800s significant resources are directed towards the control of sea lamprey using tools such as chemical treatment of larvae and trapping of the spawning adults. Understanding population structure is essential for framing a more effective sea lamprey control program. Studies using microsatellite loci have found genetic differentiation between sea lamprey from the upper and lower Great Lakes, and body size variation has been documented across the lakes, but fine-scale genetic population structure has not been studied. We use whole genome resequencing of 9-20 individuals from each of 15 sites (238 individuals) across the Great Lakes and Finger Lakes (Cayuga and Seneca), and body measurements of 9-36 individuals from each site (472 individuals), to identify population structure among and within the lakes. Genomic analyses showed structure between Lake Ontario, the Finger Lakes, and the other Great Lakes, and body size partially differentiated the lakes. Using high-resolution data to delineate spatial population structure will be important for sea lamprey control because management is most efficiently targeted when the geography of demographically independent populations is well-characterized.

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 score0.933
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
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 head0.013
GPT teacher head0.186
Teacher spread0.174 · 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
Published2021
Admission routes1
Has abstractyes

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