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Record W4402070036 · doi:10.5376/rgg.2024.15.0018

Geographical Migration and Domestication of <i>Oryza</i> Species: Tracing the Roots

2024· article· en· W4402070036 on OpenAlexvenueno aff
Yumin Huang

Bibliographic record

VenueRice Genomics and Genetics · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsnot available
Fundersnot available
KeywordsDomesticationGeographyTracingBiologyOryzaBotanyEvolutionary biologyOryza sativaEcologyGeneticsComputer scienceGene

Abstract

fetched live from OpenAlex

This study examines the geographical migration and domestication of Oryza species, focusing on Oryza sativa (Asian rice) and Oryza glaberrima (African rice). By synthesizing genetic and archaeological evidence, it traces the evolutionary paths and dispersal of these crops from wild ancestors to cultivated forms. This study highlights the complex selection processes tailored to diverse environments, which have been crucial in the adaptation and spread of rice cultivation. Studying rice's migration and domestication is essential for understanding agricultural history and genetic diversity, aiding breeding programs aimed at enhancing yield, disease resistance, and adaptability. This study also discusses the impact of independent domestication events across various regions on the genetic diversity of modern rice varieties. This study provides insights into the domestication events that have shaped one of the world's staple crops, contributing to global food security initiatives amidst changing climatic conditions.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.013
GPT teacher head0.220
Teacher spread0.207 · 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

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