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Record W2057940976 · doi:10.2135/cropsci2013.04.0210

Genetic Diversity of the Canadian Dry Bean Varieties Released Since 1930: A Pedigree Analysis

2014· article· en· W2057940976 on OpenAlexafffundabout
Alireza Navabi

Bibliographic record

VenueCrop Science · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant pathogens and resistance mechanisms
Canadian institutionsUniversity of GuelphAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsPhaseolusBiologyMesoamericaGenetic diversityRace (biology)Dry beanHorticultureGene poolPinto beanBotanyAgronomyGeographyPopulationDemography

Abstract

fetched live from OpenAlex

ABSTRACT A pedigree database of bean ( Phaseolus vulgaris L.) varieties of different market classes released in Canada since 1930 was developed. The coefficient of parentage was estimated for all pair‐wise combinations of varieties, parental and (or) ancestral genotypes. A cluster analysis was employed to study the genetic diversity of dry bean in the Canadian gene pool. The pedigree‐based estimate of genetic diversity (1 − coefficient of parentage) for all dry bean varieties released between 1930 and 2010 was 0.93. This value was smaller for varieties within each evolutionary race, estimated at 0.89 for the varieties of race Durango (pinto, Great Northern, and small red beans), 0.83 for varieties of race Mesoamerica (navy and black), and 0.76 for varieties of race Nueva Granada (kidney and cranberry beans). The results indicated a narrow genetic diversity among the Canadian beans of Andean origin (kidney and cranberry beans), suggesting that the breeding efforts for these market classes would benefit from the introduction of new genetic diversity. Among the small‐seeded beans of race Mesoamerica, varieties ‘Ex‐Rico 23’ (s yn . ICA Bunsi) and ‘Seafarer’, the medium‐sized beans of race Durango varieties ‘UI‐111’ and ‘NW‐63’, and the large‐seeded beans of race Nueva Granada varieties, ‘Montcalm’ and ‘California Dark Red Kidney’, were identified as the major progenitors of Canadian dry beans.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.634
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.013
GPT teacher head0.176
Teacher spread0.164 · 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.

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

Citations19
Published2014
Admission routes3
Has abstractyes

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