{"id":"W2736734159","doi":"10.3732/apps.1700018","title":"AveDissR: An R function for assessing genetic distinctness and genetic redundancy","year":2017,"lang":"en","type":"article","venue":"Applications in Plant Sciences","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"National Natural Science Foundation of China","keywords":"Biology; Germplasm; Redundancy (engineering); Principal component analysis; Genetics; Single-nucleotide polymorphism; Computational biology; Computer science; Artificial intelligence; Genotype; Gene; Botany","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006678057,0.00379216,0.002391332,0.003181159,0.0008095348,0.002151436,0.003450509,0.001000123,0.0227696],"category_scores_gemma":[0.02287694,0.001838321,0.003217359,0.00208974,0.001116246,0.002299401,0.002917263,0.003016485,0.02197453],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006965429,"about_ca_system_score_gemma":0.00208965,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001554181,"about_ca_topic_score_gemma":0.001314199,"domain_scores_codex":[0.996606,0.001177182,0.0003705839,0.0008560666,0.0007877713,0.0002023925],"domain_scores_gemma":[0.9916918,0.004795469,0.001142975,0.001165517,0.0009413279,0.0002629289],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003340342,0.0003588358,0.0411477,0.005807061,0.00426486,0.00174347,0.002009773,0.02349445,0.07214375,0.03221587,0.4592113,0.3542627],"study_design_scores_gemma":[0.001280525,0.0008775903,0.04352777,0.000899881,0.001473795,0.003273796,0.0003309709,0.1844259,0.09425168,0.05786518,0.6108271,0.0009659628],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01129811,0.0005329546,0.6733899,0.0003948277,0.0002665023,0.0005326611,0.0381459,0.2698132,0.005625972],"genre_scores_gemma":[0.06847799,0.0005497524,0.7556226,0.0005859808,0.000170901,0.003072456,0.05023704,0.1154403,0.005842981],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0227696,"threshold_uncertainty_score":0.07617188,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03617763012548306,"score_gpt":0.308503779180507,"score_spread":0.2723261490550239,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}