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Record W3033892804 · doi:10.11646/zootaxa.4787.1.1

Catalog of the Biting Midges of the World (Diptera: Ceratopogonidae)

2020· article· en· W3033892804 on OpenAlexaff
Art Borkent, Patrycja Dominiak

Bibliographic record

VenueZootaxa · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicVector-Borne Animal Diseases
Canadian institutionsRoyal British Columbia Museum
Fundersnot available
KeywordsCeratopogonidaeSubgenusBiologyExtant taxonSystematicsZoologyGenusTaxonomy (biology)EcologyGenealogyEvolutionary biology

Abstract

fetched live from OpenAlex

A list of all valid 6,206 extant and 296 fossil species of Ceratopogonidae described worldwide is provided, along with all their synonyms. A full citation and the country of origin of the type is given, with some larger countries also providing a more specific state or province. For the first time, worldwide, nomina dubia are identified. Numbers of species of each genus and subgenus are listed. Within subfamilies and tribes, genera are listed alphabetically. Five species have newly recognized authors, four have new names and 28 new combinations are recognized, with these listed in a table. A commentary on the state of the systematics in the family and particularly of Culicoides Latreille is given. The museums of the world are listed with the types of various authors of Ceratopogonidae species indicated. Authors providing regional catalogs, as well as summation of various collections are tabulated. The rate of description since 1758 indicates a steady progression of description, with, for example, 1,231 valid species described since the compilation of the world species by Borkent Wirth (1997), till the end of 2018. The diversity in each Region is compared and the numbers of species shared between adjacent Regions presented.

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)0.001
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.089
Threshold uncertainty score0.296

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0110.011
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0890.048

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 head0.024
GPT teacher head0.212
Teacher spread0.188 · 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
GenreOther

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

Citations247
Published2020
Admission routes1
Has abstractyes

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