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Record W4402072925 · doi:10.5376/lgg.2024.15.0019

Phylogenetic Relationships and Genetic Diversity among Domesticated Legumes

2024· article· en· W4402072925 on OpenAlexvenueno aff
Xiaoxi Zhou, Shengyu Chen

Bibliographic record

VenueLegume Genomics and Genetics · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural pest management studies
Canadian institutionsnot available
Fundersnot available
KeywordsDomesticationPhylogenetic treeGenetic diversityEvolutionary biologyPhylogenetic diversityDiversity (politics)BiologyPhylogeneticsPhylogenetic relationshipGenealogyGeneticsAnthropologySociologyGeneHistoryDemography

Abstract

fetched live from OpenAlex

The study of domesticated legumes holds significant importance due to their role in global food security and sustainable agriculture. The study aims to elucidate the phylogenetic relationships and genetic diversity among major domesticated legume species. Initially, the study presents a historical perspective on legume domestication, drawing on archaeological and evolutionary evidence. Subsequently, the study explores phylogenetic relationships using molecular markers and computational approaches, focusing on species such as the common bean ( Phaseolus vulgaris ), chickpea ( Cicer arietinum ), lentil ( Lens culinaris ), and soybean ( Glycine max ). The genetic diversity within and between these species is examined, highlighting sources of variation and their implications for crop improvement and conservation. A detailed case study on the common bean underscores the practical applications of phylogenetic and genetic diversity insights. Additionally, the study discusses the molecular tools and techniques employed in these studies, including high-throughput sequencing and bioinformatics analysis. The environmental and agricultural implications of genetic diversity and phylogenetics are considered, emphasizing their impact on crop resilience and sustainable agricultural practices. Finally, the study outlines future research directions and challenges, advocating for an integrative approach that combines traditional knowledge with modern scientific techniques. This comprehensive study underscores the critical role of understanding phylogenetic relationships and genetic diversity in advancing legume crop productivity and sustainability.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.131
Threshold uncertainty score0.507

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.021
GPT teacher head0.194
Teacher spread0.173 · 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 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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