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Toward a General Theory of Adaptive Radiation

2009· review· en· W2155029885 on OpenAlexaff
Rees Kassen

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2009
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEvolution and Genetic Dynamics
Canadian institutionsOntario GenomicsUniversity of Ottawa
Fundersnot available
KeywordsAdaptive radiationDiversification (marketing strategy)PaleobiologyEvolutionary biologyComplex adaptive systemMechanism (biology)Evolutionary theoryAdaptive strategiesEcologyPaleontologyBiologyCognitive scienceEpistemologyHistoryPhilosophyPsychologyPhylogenetics

Abstract

fetched live from OpenAlex

The history of life has been punctuated by unusually spectacular periods of evolutionary diversification called adaptive radiation. Darwin's finches in the Galapagos, cichlid fishes in African Rift and Nicaraguan crater lakes, and the emergence of mammals at the end of the Cretaceous are hallmark examples. Although we have learned much from these and other case studies about the mechanisms thought to drive adaptive radiations, convincing experimental tests of theory are often lacking for the simple reason that it is usually impossible to "rewind the tape of life," as Stephen Jay Gould was fond of saying, and run it again. This situation has changed dramatically in recent years with the increasing emphasis on the use of microbial populations which, because of their small size and rapid generation times, make possible the construction of replicated, manipulative experiments to study evolution in the laboratory. Here I review the contributions that microbial experimental evolution has made to our understanding of the ecological and genetic mechanisms underlying adaptive radiation. I focus on three major gaps in the theory of adaptive radiation--the paucity of direct tests of mechanism, the genetics of diversification, and the limits and constraints on the progress of radiations--with the aim of pointing the way toward the development of a more general theory of adaptive radiation.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.977
Threshold uncertainty score0.448

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.124
GPT teacher head0.374
Teacher spread0.250 · 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

Citations81
Published2009
Admission routes1
Has abstractyes

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