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Use of parasite and genetic markers in delineating populations of winter flounder from the central and south‐west Scotian Shelf and north‐east Gulf of Maine

2005· article· en· W2112940244 on OpenAlexaffabout
G. A. H. McClelland, Jason Melendy, Jason W. Osborne, Darrin Reid, Susan E. Douglas

Bibliographic record

VenueJournal of Fish Biology · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicParasite Biology and Host Interactions
Canadian institutionsInstitute for Marine BiosciencesFisheries and Oceans Canada
Fundersnot available
KeywordsBiologyBayFisheryPopulationAnisakis simplexNova scotiaFlounderPleuronectesZoologyEcologyFish <Actinopterygii>Oceanography

Abstract

fetched live from OpenAlex

Discriminant function analyses of infection parameters of parasitic helminths revealed that abundances of seven helminth species contributed significantly to the delineation of four host populations of winter flounder Pleuronectes americanus from the central and south‐west Scotian Shelf and the north‐east Gulf of Maine (NAFO subdivision 4WX‐5Z). These were adult digeneans, Derogenes varicus , Genolinea laticauda , Steganoderma formosum and Steringophorus furciger , metacercariae of the digenean, Stephanostomum baccatum , and larval nematodes, Anisakis simplex and Hysterothylacium aduncum . The correct classification rate was 84% overall, with Georges Bank (5Z) and Sable Island Bank (4W) winter flounder being the most accurately classified samples at 98 and 88%, respectively. Winter flounder from south‐west Nova Scotia (4X), an inshore sample from St Marys Bay and offshore fish from Browns Bank, had the lowest rates of correct classification (76 and 71%, respectively) due, primarily, to cross‐misclassification between the two samples. Winter pairwise comparisons of four microsatellite markers identified significant genetic differences between all populations sampled with the Georges Bank population being the most genetically distinct overall, and St Marys Bay and Browns Bank fish being the least dissimilar.

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)0.000
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 score0.010
Threshold uncertainty score0.518

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.030
GPT teacher head0.287
Teacher spread0.256 · 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

Citations29
Published2005
Admission routes2
Has abstractyes

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