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Record W4390459381 · doi:10.3390/agronomy14010105

Long-Term Responses to a 5.3-ka BP Climate Event and the Absolute Dominance of Foxtail Millet in Early Longshan (4800–4300 BP), Southern Loess Plateau, China

2023· article· en· W4390459381 on OpenAlexfundno aff
Zejuan Sun, Xiaoyi Wang, Xiaojuan Wang, Qingzhu Wang, Yang Liu, Bingyan Wang, Lin Guo, Xuexiang Chen

Bibliographic record

VenueAgronomy · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
FundersNational Social Science Fund of ChinaJiangsu Normal UniversityHenan UniversityUniversity of TorontoSichuan UniversityMinistry of Science and Technology of the People's Republic of China
KeywordsFoxtailClimate changeGeographyDominance (genetics)Subsistence agricultureAgricultureEcologyBiologyArchaeology

Abstract

fetched live from OpenAlex

Abrupt climate events profoundly impact human societies, both environmentally and socially. However, existing research predominantly concentrates on immediate responses, overlooking long-term consequences. This study, centered on the Guojiazaoyuan site in the southern Loess Plateau, explores the enduring effects of a 5.3-ka BP climate event that transformed the local subsistence system. Through detailed analysis of archaeobotanical evidence, specifically floral remains dating to 4800–4300 BP obtained via flotation, significant post-event shifts in agricultural practices and food strategies are revealed. Notably, there is a clear prioritization of foxtail millet cultivation, a shift towards diversified food sources, and the introduction of new livestock. These changes represent strategic adaptations aimed at bolstering resilience and reducing vulnerability to future climatic challenges. The southern Loess Plateau developed an agricultural pattern with foxtail millet as the dominant crop, although different patterns were observed in surrounding regions during the early Longshan period (4800–4300 BP). Emphasizing the importance of a long-term perspective, particularly in agriculture and food security, the findings contribute to a broader understanding of how ancient societies coped with environmental changes. These insights are pertinent to ongoing discussions on climate resilience and sustainable agriculture.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.014
GPT teacher head0.249
Teacher spread0.235 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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