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Saga from the Prehistoric Graveyards: Ancient DNA Technology is rewriting the population history of the Indian subcontinent

2020· article· en· W4386493698 on OpenAlexaff
Pallab Sarkar

Bibliographic record

VenueIndian Science Cruiser · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicForensic and Genetic Research
Canadian institutionsLa Cité Collégiale
Fundersnot available
KeywordsAryan racePrehistoryBronze AgeHomo sapiensPopulationAncient DNAIndusAncient historyGeographyIndian subcontinentArchaeologyCivilizationHaplogroupSteppeHistoryEthnologyBiologyPaleontologyHaplotypeDemographyGenetics

Abstract

fetched live from OpenAlex

The present population of the Indian subcontinent has been formed by the Homo sapiens who migrated to this land as a part of the Out of Africa (OOA) migration [approximately 65000 years before present (YBP)] and multiple other migrations viz., the so called ‘Aryan’ migration (3500-4000 YBP). Analysis of the Indus Valley Civilization fossils using recently developed ‘ancient DNA technology’ revealed no Pontic steppe DNA (Aryan / Yamnaya DNA) and they are found to be the genetic stock of the most people living in subcontinent today. In contrast, at least 17.5% modern North Indians (mostly Brahmins) bear the Y chromosome marker (R1a haplogroups) from the Eurasian steppe, indicating a heavily sex biased (male dominated) infiltration during Bronze age. This finding substantially established Aryan migration in the Indian subcontinent.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.421
Threshold uncertainty score0.527

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.023
GPT teacher head0.251
Teacher spread0.228 · 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 designBench or experimental
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
Published2020
Admission routes1
Has abstractyes

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