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Record W3094219706 · doi:10.1101/2020.10.21.348599

The genetic and linguistic structures of Abyssinians and their neighbor reveal the historical demographic dynamics and environmental adaptation in the African Horn region

2020· preprint· en· W3094219706 on OpenAlexaff
Demissew Sertse, Tesfaye B. Mersha, Jemaneh Habtewold

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2020
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicForensic and Genetic Research
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of Ottawa
Fundersnot available
KeywordsGenetic diversityInternational HapMap ProjectGenetic structureGeographyPopulationEvolutionary biologyEthnologySingle-nucleotide polymorphismBiologyHistoryDemographyGeneticsGenotypeSociologyGene

Abstract

fetched live from OpenAlex

Abstract The African Horn region that includes the Abyssinian is one of the areas in the world that harbor high human genetic diversity manifesting past intermingling of people of different origins attributed to its geographic immediacy to the middle east and being historical trade and religio-cultural hub. Here, we performed a genetic structure analysis of linguistically differentiated populations of Ethiopia, South Sudan, and Somali. To get insight into the genetic landscape of the horn of Africa against the rest of the world, we leverage HapMap SNPs data from Utah residents with Northern and Western European ancestry (CEU), Maasai (MKK), and Yoruba (YRI) and analyzed for genetic admixture and diversity. The genetic and linguistic affiliations mismatch for most Cushitic and Semitic language speakers. The gradients of genetic variations among the different sub-populations within the region show gene-flow directions and past mass population movements. Ethiopians that predominately inhabited the central and northern Ethiopia harbored ~10-15% of CEU admixture. The African horn ancestral line contributed a total of ~20%, 5%, and 2% to MKK, YRI, and CEU, respectively. MKK showed a high genetic diversity comparable to the Ethiopian Cushitic, Semitic, and North Omotic language speakers. Allelic distribution frequencies among the populations at some outlier loci may also provide insight into the adaptations to critical environmental factors such as Malaria.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.776
Threshold uncertainty score0.581

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.011
GPT teacher head0.204
Teacher spread0.192 · 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.

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

Citations2
Published2020
Admission routes1
Has abstractyes

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