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Record W2138265704 · doi:10.1098/rspb.2009.1326

Long-term changes in metapopulation genetic structure: a quarter-century retrospective study on low-Arctic rock pool<i>Daphnia</i>

2009· article· en· W2138265704 on OpenAlexafffundabout
Lawrence J. Weider, Dagmar Frisch, Paul D. N. Hebert

Bibliographic record

VenueProceedings of the Royal Society B Biological Sciences · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsUniversity of Guelph
FundersCanadian Nuclear Safety CommissionUniversity of GuelphNatural Sciences and Engineering Research Council of CanadaUniversity of Oklahoma
KeywordsMetapopulationDaphniaTerm (time)ArcticQuarter (Canadian coin)EcologyGeologyOceanographyBiologyGeographyDemographyArchaeologySociologyPopulationPhysicsZooplanktonAstronomy

Abstract

fetched live from OpenAlex

Population genetic surveys approximately 25 years apart examined the distribution and abundance of asexual clones of the freshwater zooplankter Daphnia pulex complex in rock pools near Churchill, Manitoba, Canada. In 1984-1985, melanic members of this species complex were present in 131 rock pools at this site, but were only detected in 90 of these pools in 2007-2008. Allozymic surveys conducted during these two time periods revealed that 59 per cent of these populations showed unchanged clonal composition. Total clonal replacement occurred in 8 per cent of the populations, while the others (33%) included a mixture of 'resident' clones and new 'colonists'. We discuss these changes in light of shifts in biotic and abiotic factors. We also discuss the use of rock pool habitats as 'sentinel' systems for examining long-term environmental changes in the ecological genetics of aquatic organisms in the Arctic.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.099
Threshold uncertainty score0.196

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.248
Teacher spread0.233 · 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

Citations21
Published2009
Admission routes3
Has abstractyes

Explore more

Same venueProceedings of the Royal Society B Biological Sciences→Same topicGenetic diversity and population structure→French-language works237,207→