MétaCan
Menu
← Back to cohort
Record W4241220149 · doi:10.1002/9781118945568.ch3

Insect Biodiversity in the Nearctic Region

2017· other· en· W4241220149 on OpenAlexaff
H. V. Danks, Andrew B. T. Smith

Bibliographic record

Venuenot available
Typeother
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsCanadian Museum of Nature
Fundersnot available
KeywordsNearctic ecozoneBiodiversityEcologyTaxonExtant taxonBiologyEntomologyInsectHabitatGlobal biodiversityGeographyGenusEvolutionary biology

Abstract

fetched live from OpenAlex

The Nearctic region has lower insect biodiversity relative to other biogeographical realms and is most similar faunistically to the Palearctic region, with many overlapping taxa at the lower taxonomic levels (genera and species). This chapter examines the biodiversity of insects in the Nearctic region, based on extant species, and the state of knowledge about them. Nevertheless, a tremendous amount of insect biodiversity exists in the Nearctic region, including endemic families such as the Pleocomidae and Diphyllostomatidae (Coleoptera), with low overlap, at the species and genus levels, with insects in other realms. The importance of entomology and the study of insect biodiversity emerged in North America during the 1800s. Conservation of natural habitats and protection of species at risk are strong desires of people across North America. The chapter tabulates the numbers of species of insects estimated to occur in the Nearctic region.

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: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.026
GPT teacher head0.230
Teacher spread0.203 · 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

Citations7
Published2017
Admission routes1
Has abstractyes

Explore more

Same topicEcology and Vegetation Dynamics Studies→French-language works237,207→