MétaCan
Menu
Back to cohort

DIVERSITY OF SPIDERS IN BOREAL AND ARCTIC ZONES

2002· article· en· W2115918348 on OpenAlexaboutno aff
Yuri M. Marusik, Seppo Koponen

Bibliographic record

VenueJournal of Arachnology · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSpider Taxonomy and Behavior Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFaunaEcologySpiderArcticBorealNearctic ecozoneTaxonRange (aeronautics)BiologyBiodiversityTaigaSpecies diversityGeographyTaxonomy (biology)

Abstract

fetched live from OpenAlex

During the last two decades a great number of studies dealing with arctic and boreal spiders have been published, both in the Palaearctic and the Nearctic. Such an increase in information makes it possible to analyze basic patterns of spider diversity in the North as well as to show areas where further studies are still necessary. The number of species found in faunas of larger areas north of 60°N varies from 620 (Finland) to 250 (Polar Urals) and 300 (Yukon), when island faunas are excluded. Two areas, divided by the Bering Strait, Northeastern Siberia and north-western North America have marked proportion of endemic taxa (ca. 8 %) belonging to several spider families. Considerable number of endemic spiders are known also in Middle Siberia. The number of spiders in local faunas of the boreal zone varies around 300 species. Study of species composition in more than 20 local northern faunas reveals that proportion of Lycosidae species in each local fauna varies in smallest range (7–12 % of all species found) in comparison to other families. Thus Lycosidae can be used as an indicator group of general species diversity of spiders in local faunas.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.234
Teacher spread0.210 · 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

Citations33
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueJournal of ArachnologySame topicSpider Taxonomy and Behavior StudiesFrench-language works237,207