MétaCan
Menu
Back to cohort
Record W1967519360 · doi:10.1080/14634980802523140

The distribution of the invasive New Zealand mud snail (<i>Potamopyrgus antipodarum</i>) in Lake Ontario

2008· article· en· W1967519360 on OpenAlexaffabout
Edward P. Levri, Ron M. Dermott, Shane J. Lunnen, Ashley A. Kelly, Thomas Ladson

Bibliographic record

VenueAquatic Ecosystem Health & Management · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Invertebrate Ecology and Behavior
Canadian institutionsFisheries and Oceans Canada
FundersPennsylvania State UniversityWashington State University
KeywordsSnailInvasive speciesDreissenaFisheryRange (aeronautics)BiologyPopulationPopulation densityEcologyMolluscaBivalviaDemography

Abstract

fetched live from OpenAlex

The invasive New Zealand mud snail, Potamopyrgus antipodarum, is a world-wide invasive species currently found in Europe, Australia, Japan, and, most recently, North America. It was first discovered in Lake Ontario in 1991. The purposes of this study were to update the current known geographic distribution of the snail, determine the relationship between depth and population densities, and examine the relationship between Potamopyrgus and dreissenid mussel densities in Lake Ontario. We sampled several locations in Lake Ontario and determined that the range of Potamopyrgus has expanded. However, densities appear to have moderated in the past ten years. In one location (Wilson, NY), the densities of the snail are dependent upon depth with highest densities occurring between 15 and 25 m. At this location, no snails were found at depths of less than 15 m. We found no correlation between the densities of Potamopyrgus and invasive mussels. The reasons for apparent reduction in densities over time and the apparent lack of Potamopyrgus in shallow water are discussed.

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)0.001
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 score0.895
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.014
GPT teacher head0.218
Teacher spread0.204 · 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

Citations20
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueAquatic Ecosystem Health & ManagementSame topicAquatic Invertebrate Ecology and BehaviorFrench-language works237,207