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Record W2143668942 · doi:10.11646/zootaxa.1668.1.24

Weevils, weevils, weevils everywhere*

2007· article· en· W2143668942 on OpenAlexaff
Rolf G. Oberprieler, Adriana E. Marvaldi, Robert S. Anderson

Bibliographic record

VenueZootaxa · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicColeoptera Taxonomy and Distribution
Canadian institutionsCanadian Museum of Nature
FundersConsejo Nacional de Investigaciones Científicas y TécnicasCommonwealth Scientific and Industrial Research Organisation
KeywordsBiologyCurculionidaeWeevilTaxonomy (biology)PhylogeneticsPhylogenetic treeZoologyEcologyEvolutionary biologyBotany

Abstract

fetched live from OpenAlex

An overview is presented of the progress made on the taxonomy, classification and phylogeny of weevils in the 250 years since the first taxonomic descriptions of weevils by Carolus Linnaeus. The number of described weevils species is calculated to be about 62 000 and the likely total number of existing species 220 000, indicating that we have described just over a quarter of the diversity of this important group of beetles and that, at current rates of discovery and description, it will take another 650 years or so to describe the rest. Within the framework of the current concept of weevil phylogeny, a brief account is given of the seven main weevil lineages (families), and of the subfamilies of the largest of them, the Curculionidae, summarising their diversity, distribution and biology and identifying the major classificatory problems remaining in each. In conjunction with the phylogenetic hypothesis of weevil relationships and their fossil record, which is briefly summarised, the evolutionary history of weevils is mapped as a sequence of key evolutionary innovations that together have led to the phenomenal diversification and success of weevils.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0160.005

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 head0.020
GPT teacher head0.222
Teacher spread0.202 · 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

Citations341
Published2007
Admission routes1
Has abstractyes

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