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Record W3028330901 · doi:10.1371/journal.pone.0229372

Southwest Asian cereal crops facilitated high-elevation agriculture in the central Tien Shan during the mid-third millennium BCE

2020· article· en· W3028330901 on OpenAlexfundno aff
Giedrė Motuzaitė Matuzevičiūtė, Taylor R. Hermes, Basira Mir-Makhamad, Kubatbek Tabaldiev

Bibliographic record

VenuePLoS ONE · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicPacific and Southeast Asian Studies
Canadian institutionsnot available
FundersLietuvos Mokslo TarybaQueen's UniversityQueen's University Belfast
KeywordsElevation (ballistics)AgricultureGeographyCentral asiaAgronomyBiologyAgroforestryPhysical geographyArchaeology

Abstract

fetched live from OpenAlex

We report the earliest and the most abundant archaeobotanical assemblage of southwest Asian grain crops from Early Bronze Age Central Asia, recovered from the Chap II site in Kyrgyzstan. The archaeobotanical remains consist of thousands of cultivated grains dating to the mid-late third millennium BCE. The recovery of cereal chaff and weeds suggest local cultivation at 2000 m.a.s.l., as crops first spread to the mountains of Central Asia. The site's inhabitants possibly cultivated two types of free-threshing wheats, glume wheats, and hulled and naked barleys. Highly compact caryopses of wheat and barley grains represent distinct morphotypes of cereals adapted to highland environments. While additional macrobotanical evidence is needed to confirm the presence of glume wheats at Chap II, the possible identification of glume wheats at Chap II may represent their most eastern distribution in Central Asia. Based on the presence of weed species, we argue that the past environment of Chap II was characterized by an open mountain landscape, where animal grazing likely took place, which may have been further modified by people irrigating agricultural fields. This research suggests that early farmers in the mountains of Central Asia cultivated compact morphotypes of southwest Asian crops during the initial eastward dispersal of agricultural technologies, which likely played a critical role in shaping montane adaptations and dynamic interaction networks between farming societies across highland and lowland cultivation zones.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.465
Threshold uncertainty score0.634

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.039
GPT teacher head0.225
Teacher spread0.187 · 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 designQualitative
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
Published2020
Admission routes1
Has abstractyes

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