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Record W2012340164 · doi:10.4141/p99-115

Molecular analysis of genetic variation among alfalfa (<i>Medicago sativa</i> L.) and <i>Medicago ruthenica</i> clones

2000· article· en· W2012340164 on OpenAlexvenueno aff
T. A. Campbell

Bibliographic record

VenueCanadian Journal of Plant Science · 2000
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Taxonomy and Phylogenetics
Canadian institutionsnot available
FundersMaryland Sea Grant, University of Maryland
KeywordsBiologyRAPDMedicago sativaMedicagoMicrosatelliteGenetic variationBotanyGenetic diversityPopulationGeneticsGeneAllele

Abstract

fetched live from OpenAlex

Medicago ruthenica (L.) Ledebour is an allogamous diploid (2n = 2x = 16) perennial indigenous to Siberia, Mongolia and Manchuria with a remarkable ability to survive mechanical and physiological stress. The possibility of hybridizing alfalfa (Medicago sativa L.) and M. ruthenica is being investigated. The objective of the current research was to conduct a molecular assessment of genetic relatedness and inter- and intra-specific genetic variation in cultivated alfalfa (2n = 4x = 32) and M. ruthenica. Seventeen alfalfa clones, selected randomly from the broad-based population W10- AC3, and 17 agronomically superior M. ruthenica clones, tracing to 17 collection sites in Inner Mongolia, were studied using Random Amplified Polymorphic DNA (RAPD), Anchored Microsatellite Priming (AMSP), and Simple Sequence Repeat (SSR) analyses of genomic DNA. Mean genetic distances (GD) within M. ruthenica and alfalfa clones were 0.5 and 0.56, respectively, based on RAPD/AMSP data, and 0.29 and 0.40, respectively, based on SSR data. Alfalfa and M. ruthenica were genetically distant (RAPD/AMSP GD = 0.73); however, this difference does not necessarily preclude the possibility of interspecific hybridization, although the use of techniques such as bridge crossing, embryo culture rescue and/or protoplast fusion may be necessary. Key words: Alfalfa, genetic resources, Medicago ruthenica, Medicago sativa, microsatellite, simple sequence

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.456
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.008
GPT teacher head0.174
Teacher spread0.166 · 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

Citations8
Published2000
Admission routes1
Has abstractyes

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