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Record W2053603356 · doi:10.1177/0959683613518595

The evolution of millet domestication, Middle Yellow River Region, North China: Evidence from charred seeds at the late Upper Paleolithic Shizitan Locality 9 site

2014· article· en· W2053603356 on OpenAlexaff
Sheahan Bestel, Gary W. Crawford, Li Liu, Jinming Shi, Yanhua Song, Xingcan Chen

Bibliographic record

VenueThe Holocene · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicPacific and Southeast Asian Studies
Canadian institutionsUniversity of Toronto
FundersNational Academy of Sciences of UkraineAustralian Research CouncilLa Trobe University
KeywordsPhytolithDomesticationFoxtailSetariaBiologyGeographyChinaMacrofossilStipaBotanyArchaeologyPollenEcology

Abstract

fetched live from OpenAlex

Charred grass seeds recovered by flotation from the late Upper Paleolithic Shizitan Locality 9 site in Shanxi province, China, are examined in relation to claims based on starch grain and phytolith analysis of early millet domestication and Neolithic plant foods in North China. Small numbers of wild millet (Paniceae tribe) grasses and goosefoot ( Chenopodium sp.) seeds provide the first specific macrobotanical evidence for the association of these important plants with people in China during the late Paleolithic. Wild Setaria and Echinochloa spp. are present between 13,800 and 11,600 cal. BP, almost 4000 years before the earliest evidence of unequivocally domesticated millet macrofossils in the Yellow River region by c. 8000–7600 cal. BP. In fact, seed evidence for the process of foxtail millet domestication in North China has not been available until now, and these are the only late Upper Paleolithic seeds ever recovered from North China. This study suggests that domestication-related traits in foxtail millet were gradually established over several millennia.

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 score0.079
Threshold uncertainty score0.157

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.026
GPT teacher head0.255
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 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

Citations44
Published2014
Admission routes1
Has abstractyes

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