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Contrasting Patterns of Nuclear and mtDNA Diversity in Native American Populations

2010· article· en· W1592828382 on OpenAlexaff
Ning Yang, Stéphane Mazières, Cláudio M. Bravi, Nicolas Ray, Sijia Wang, Mari‐Wyn Burley, Gabriel Bedoya, Winston Rojas, María Victoria Parra, Julio A. Molina, Carla Gallo, Giovanni Poletti, Kim Hill, Ana Hurtado, Maria Luiza Petzl‐Erler, Luiza Tamie Tsuneto, William Klitz, Ramiro Barrantes, Elena Llop, Francisco Rothhammer, Damian Labuda, Francisco M. Salzano, María Cátira Bortolini, Laurent Excoffier, Jean Michel Dugoujon, Andrés Ruiz‐Linares

Bibliographic record

VenueAnnals of Human Genetics · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicForensic and Genetic Research
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsPopulationDivergence (linguistics)GeographyEvolutionary biologyAutosomeEffective population sizeBiologyEcologyGenetic diversityDemographyChromosomeGenetics

Abstract

fetched live from OpenAlex

We report an integrated analysis of nuclear (autosomal, X- and Y-chromosome) short tandem repeat (STR) data and mtDNA D-loop sequences obtained in the same set of 22 Native populations from across the Americas. A north to south gradient of decreasing population diversity was observed, in agreement with a settlement of the Americas from the extreme northwest of the continent. This correlation is stronger with "least cost distances," which consider the coasts as facilitators of migration. Continent-wide estimates of population structure are highest for the Y-chromosome and lowest for the autosomes, consistent with the effective size of the different marker systems examined. Population differentiation is highest in East South America and lowest in Meso America and the Andean region. Regional analyses suggest a deviation from mutation-drift equilibrium consistent with population expansion in Meso America and the Andes and population contraction in Northwest and East South America. These data hint at an early divergence of Andean and non-Andean South Americans and at a contrasting demographic history for populations from these regions.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
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 head0.076
GPT teacher head0.365
Teacher spread0.290 · 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

Citations60
Published2010
Admission routes1
Has abstractyes

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