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Record W4401241315 · doi:10.5376/rgg.2024.15.0010

From Wild to Cultivated: The Domestication Pathways of Asian Cultivated Rice (<i>Oryza sativa</i> L.)

2024· article· en· W4401241315 on OpenAlexvenueno aff
Lijuan Chen

Bibliographic record

VenueRice Genomics and Genetics · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGABA and Rice Research
Canadian institutionsnot available
Fundersnot available
KeywordsDomesticationOryza rufipogonIntrogressionOryza sativaBiologyGene flowGenetic diversitySubspeciesJaponicaOryzaGene poolAgricultureBotanyGeneGenetic variationPopulationGeneticsEcology

Abstract

fetched live from OpenAlex

The domestication of rice (commonly known as Asian cultivated rice) is a pivotal event in agricultural history, significantly impacting global food security. This review synthesizes current research on the pathways of rice domestication, with a focus on genetic and geographic origins, the role of wild ancestors, and the evolutionary processes involved. Multiple studies indicate that Oryza sativa was independently domesticated from different populations of its wild ancestor, Oryza rufipogon, in various regions of Asia, including southern China, India, and Indochina. Genetic analyses reveal that the two main subspecies, indica and japonica, underwent separate domestication events, followed by gene flow between them. Additionally, the domestication process involved significant genetic changes, such as reduced seed shattering and dormancy, which are crucial for effective cultivation and harvest. This study also explores the impact of human-directed breeding and introgression on the genetic diversity of domesticated rice.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.022
GPT teacher head0.248
Teacher spread0.226 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

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