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Differentiation between subpopulations of a polychromatic damselfly with respect to morph frequencies, but not neutral genetic markers

2003· article· en· W2032528201 on OpenAlexaffabout
Alex Wong, Myron L. Smith, Mark R. Forbes

Bibliographic record

VenueMolecular Ecology · 2003
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsCarleton University
Fundersnot available
KeywordsBiologyDamselflyTraitLocus (genetics)OdonataAlleleGenetic driftSelection (genetic algorithm)Evolutionary biologyGeneticsGenetic variationZoologyGene

Abstract

fetched live from OpenAlex

The damselfly, Nehalennia irene (Hagen), has two distinct female colour morphs. Individuals of one morph have male-like colouration and pattern (androchromes), whereas gynochromes are different from males and androchromes in these respects. In several damselflies, such female-limited polychromatism is attributable to a single genetic locus. We developed six polymorphic genetic markers, which were codominant, to test for genetic differentiation in N. irene, collected from two sites located 8 km from one another in eastern Ontario, Canada. Based on three censuses spanning a 10 year period (1992-2001), morph ratios differed consistently and significantly between these two sites. However, subpopulations at these sites were not genetically differentiated with respect to the putatively neutral markers. Our results suggest that site differences in morph ratios of female N. irene cannot be explained by genetic drift, but are consistent with spatially variable selection operating on different morphs, perhaps mediated by male density. Alternatively, morph type may be a plastic trait and cues for induction may differ between sites.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.559
Threshold uncertainty score0.200

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 head0.018
GPT teacher head0.221
Teacher spread0.203 · 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

Citations35
Published2003
Admission routes2
Has abstractyes

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