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Record W2768917784 · doi:10.1098/rspb.2017.1540

Genome diversity in the Neolithic Globular Amphorae culture and the spread of Indo-European languages

2017· article· en· W2768917784 on OpenAlexaff
Francesca Tassi, Stefania Vai, Silvia Ghirotto, Martina Lari, Alessandra Modi, Elena Pilli, Andrea Brunelli, Roberta Rosa Susca, Alicja Budnik, Damian Labuda, Federica Alberti, Carles Lalueza‐Fox, David Reich, David Caramelli, Guido Barbujani

Bibliographic record

VenueProceedings of the Royal Society B Biological Sciences · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicForensic and Genetic Research
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
FundersNational Institute of General Medical SciencesH2020 European Research CouncilUniversità degli Studi di FerraraMinistero dell’Istruzione, dell’Università e della RicercaMinisterio de Economía y Competitividad
KeywordsSteppeGeographyDiversity (politics)Ancient historyEvolutionary biologyArchaeologyBiologyEthnologyZoologyHistoryAnthropologySociology

Abstract

fetched live from OpenAlex

It is unclear whether Indo-European languages in Europe spread from the Pontic steppes in the late Neolithic, or from Anatolia in the Early Neolithic. Under the former hypothesis, people of the Globular Amphorae culture (GAC) would be descended from Eastern ancestors, likely representing the Yamnaya culture. However, nuclear (six individuals typed for 597 573 SNPs) and mitochondrial (11 complete sequences) DNA from the GAC appear closer to those of earlier Neolithic groups than to the DNA of all other populations related to the Pontic steppe migration. Explicit comparisons of alternative demographic models via approximate Bayesian computation confirmed this pattern. These results are not in contrast to Late Neolithic gene flow from the Pontic steppes into Central Europe. However, they add nuance to this model, showing that the eastern affinities of the GAC in the archaeological record reflect cultural influences from other groups from the East, rather than the movement of people.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.004
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.025
GPT teacher head0.280
Teacher spread0.255 · 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

Citations38
Published2017
Admission routes1
Has abstractyes

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