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Ancient lakes revisited: from the ecology to the genetics of speciation

2010· review· en· W1595517310 on OpenAlexafffund
Melania E. Cristescu, Sarah J. Adamowicz, James J. Vaillant, Douglas Haffner

Bibliographic record

VenueMolecular Ecology · 2010
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsUniversity of GuelphUniversity of Windsor
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGenetic algorithmBiologyReproductive isolationEcological speciationEcologyIncipient speciationGene flowEvolutionary biologyEcological nicheIntrogressionHabitatPopulationGeneGeneticsGenetic variation

Abstract

fetched live from OpenAlex

Explosive speciation in ancient lakes has fascinated biologists for centuries and has inspired classical work on the tempo and modes of speciation. Considerable attention has been directed towards the extrinsic forces of speciation--the geological, geographical and ecological peculiarities of ancient lakes. Recently, there has been a resurgence of interest in the intrinsic nature of these radiations, the biological characteristics conducive to speciation. While new species are thought to arise mainly by the gradual enhancement of reproductive isolation among geographically isolated populations, ancient lakes provide little evidence for a predominant role of geography in speciation. Recent phylogenetic work provides strong evidence that multiple colonization waves were followed by parallel intralacustrine radiations that proceeded at relatively rapid rates despite long-term gene flow through hybridization and introgression. Several studies suggest that hybridization itself might act as a key evolutionary mechanism by triggering major genomic reorganization/revolution and enabling the colonization of new ecological niches in ancient lakes. These studies propose that hybridization is not only of little impediment to diversification but could act as an important force in facilitating habitat transitions, promoting postcolonization adaptations and accelerating diversification. Emerging ecological genomic approaches are beginning to shed light on the long-standing evolutionary dilemma of speciation in the face of gene flow. We propose an integrative programme for future studies on speciation in ancient lakes.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.943
Threshold uncertainty score0.783

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.016
GPT teacher head0.269
Teacher spread0.253 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations117
Published2010
Admission routes2
Has abstractyes

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