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Record W2269871837 · doi:10.4141/cjps2012-097

Genetic and phenotypic variation in<i>Lotus japonicus</i>(Regel) K. Larsen, a model legume species

2013· article· en· W2269871837 on OpenAlexvenueno aff
M. Mimura

Bibliographic record

VenueCanadian Journal of Plant Science · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyLotus japonicusMantel testGenetic variationEcologyPopulationPhylogeographyEvolutionary biologyPhylogeneticsGeneticsGeneDemography

Abstract

fetched live from OpenAlex

Mimura, M. 2013. Genetic and phenotypic variation in Lotus japonicus (Regel) K. Larsen, a model legume species. Can. J. Plant Sci. 93: 435–444. Lotus japonicus is a model legume species with more than 90% of its gene space determined; however, its ecological and evolutionary background is little known. The genetic and phenotypic variation of this model species was investigated within the Japanese Archipelago, where it exists in various climates and has experienced repeated vegetative shifts in conjunction with historical climate changes, using nuclear microsatellite loci and common garden experiments. The partial Mantel test was performed to detect the influence of phylogeographic effects on phenotypic variation among accessions along environmental gradients. Western Japan showed more complex genetic population structures than northern Japan, which may reflect past population dynamics. The total biomass demonstrated clinal variation with a climatic variable (ClimatePC). The trend was significant in a partial Mantel test when controlling for genetic distance, which is independent of the environmental distance. This suggests adaptive divergence within the Japanese Archipelago. With highly accessible genome information, L. japonicus appears to be a promising species for future ecological and evolutionary studies.

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: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

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

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 head0.010
GPT teacher head0.185
Teacher spread0.175 · 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

Citations3
Published2013
Admission routes1
Has abstractyes

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