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Record W7161956332 · doi:10.82308/44352

Genetic analysis of «Pardosa» wolf spiders (Aranae: Lycosidae) across the northern Nearctic

2013· dissertation· en· W7161956332 on OpenAlexaboutno aff
Kathrin Sim

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSpider Taxonomy and Behavior Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNearctic ecozoneBeringiaArcticPhylogeographyBiological dispersalPopulation

Abstract

fetched live from OpenAlex

An analysis of the genetic structure of northern Nearctic wolf spiders from the genus Pardosa (Lycosidae) was conducted. Wolf spiders are common and abundant across the Nearctic, but despite their ecological importance, little is known about their phylogeography and taxonomically uncertain species exist. Wolf spiders were collected from sites across northern Canada to examine the phylogeographic history of Pardosa glacialis (Thorell) and taxonomic status of the Nearctic members of the Pardosa lapponica species-group. Results show that the high Arctic species P. glacialis occupied two major glacial refugia during the Wisconsin glaciation: Beringia and a lesser-known high Arctic refugium. Additionally, analyses support a P. glacialis population expansion in Beringia during the Wisconsin glaciation, likely facilitated by an increase in habitat due to suitable climate in the region. Post-glacial dispersal from the Beringian and high Arctic refugia produced a secondary contact zone in central high Arctic Canada. With regards to taxonomy, morphometric analyses of P. lapponica (Thorell) and P. concinna (Thorell), the only two members of the P. lapponica species-group in the Nearctic, revealed no species-specific variation beyond a single male morphological character. Genetic analyses showed there was more genetic variation between Palearctic and Nearctic P. lapponica specimens than between Nearctic P. lapponica and P. concinna specimens. The P. lapponica species-group is in need of taxonomic revision to resolve the species boundaries among its members.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.130
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.284
Teacher spread0.271 · 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 teacher head, not a consensus.

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

Citations0
Published2013
Admission routes1
Has abstractyes

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