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Record W2140643163 · doi:10.1146/annurev.ento.45.1.1

The Current State Of Insect Molecular Systematics: A Thriving Tower of Babel

2000· review· en· W2140643163 on OpenAlexaff
Michael S. Caterino, Soowon Cho, Felix A. H. Sperling

Bibliographic record

VenueAnnual Review of Entomology · 2000
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLepidoptera: Biology and Taxonomy
Canadian institutionsUniversity of Alberta
FundersDivision of Agriculture and Natural Resources, University of CaliforniaNational Science Foundation
KeywordsBiologySystematicsEvolutionary biologyInsectPhylogeneticsMolecular phylogeneticsPhylogenomicsPhylogenetic treeTaxonDNA sequencingEcologyCladeGeneZoologyTaxonomy (biology)Genetics

Abstract

fetched live from OpenAlex

Insect molecular systematics has undergone remarkable recent growth. Advances in methods of data generation and analysis have led to the accumulation of large amounts of DNA sequence data from most major insect groups. In addition to reviewing theoretical and methodological advances, we have compiled information on the taxa and regions sequenced from all available phylogenetic studies of insects. It is evident that investigators have not usually coordinated their efforts. The genes and regions that have been sequenced differ substantially among studies and the whole of our efforts is thus little greater than the sum of its parts. The cytochrome oxidase I, 16S, 18S, and elongation factor-1 alpha genes have been widely used and are informative across a broad range of divergences in insects. We advocate their use as standards for insect phylogenetics. Insect molecular systematics has complemented and enhanced the value of morphological and ecological data, making substantial contributions to evolutionary biology in the process. A more coordinated approach focused on gathering homologous sequence data will greatly facilitate such efforts.

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)0.006
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.008
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0040.005
Science and technology studies0.0020.005
Scholarly communication0.0050.013
Open science0.0020.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0080.006

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 head0.023
GPT teacher head0.323
Teacher spread0.300 · 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 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

Citations548
Published2000
Admission routes1
Has abstractyes

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