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Record W2999271645 · doi:10.1139/cjes-2018-0189

Ancient DNA reveals northwest range extension of Richardson’s ground squirrel (<i>Urocitellus richardsonii</i>) into northeastern British Columbia, Canada, during the Late Pleistocene

2020· article· en· W2999271645 on OpenAlexafffundvenueabout
Thomas C.A. Royle, Dongya Yang, Jonathan C. Driver

Bibliographic record

VenueCanadian Journal of Earth Sciences · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsSimon Fraser University
FundersSocial Sciences and Humanities Research Council of CanadaSimon Fraser University
KeywordsPleistoceneGround squirrelRange (aeronautics)Mitochondrial DNAArchaeologyVegetation (pathology)Glacial periodGeologyAncient DNAGeographyPaleontologyEcologySquirrel monkeyBiology

Abstract

fetched live from OpenAlex

Ancient DNA was extracted from 12 500 to 10 500 year old ground squirrel bones from Tse’K’wa, an archaeological site in the Peace River region of northeastern British Columbia, Canada. Analysis of mitochondrial DNA from seven individuals demonstrates that all are Urocitellus richardsonii (Richardson’s ground squirrel), a species not found in the region today. Phylogenetic and sequence analyses indicate these individuals share a previously undocumented mitochondrial control region haplotype that is most closely related to haplotypes observed in modern specimens from Saskatchewan and Montana. At the end of the Pleistocene these ground squirrels extended their range north and west into open vegetation communities that developed when ice sheets melted and glacial lakes drained. They were subsequently extirpated from the Peace River region when forests replaced earlier pioneering vegetation communities.

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 score0.277
Threshold uncertainty score0.558

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.012
GPT teacher head0.193
Teacher spread0.181 · 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

Citations1
Published2020
Admission routes4
Has abstractyes

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