{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001001776,0.00007090059,0.00006151228,0.00003461365,0.000865992,0.000182968,0.0002654523,0.00006189393,0.00000360968],"category_scores_gemma":[0.00002732638,0.00006568372,0.00001525151,0.00004076911,0.0002453161,0.00001492337,0.00006042016,0.00002665123,7.188121e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000335126,"about_ca_system_score_gemma":0.00003528681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003324475,"about_ca_topic_score_gemma":0.0001333104,"domain_scores_codex":[0.9993742,0.00001425868,0.0001037294,0.0003101265,0.0000752444,0.0001224494],"domain_scores_gemma":[0.9995631,0.00001200672,0.00009239517,0.0002610075,0.00002779856,0.00004367368],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002657527,0.00005559499,0.9093125,0.00003503193,0.00001089829,7.436333e-7,0.0001021885,0.000766355,0.04069535,0.002737562,0.0002963301,0.04596087],"study_design_scores_gemma":[0.0001743158,0.00006322117,0.9851887,0.000005882717,0.00001297959,0.00001089835,0.0001549584,0.0008382306,0.001214058,0.00267529,0.009546444,0.0001150639],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9701706,0.0002077889,0.02880155,0.00007870587,0.0000927716,0.0002450574,0.00004752377,0.000005275339,0.0003506792],"genre_scores_gemma":[0.9883592,0.00005836999,0.01123429,0.00003188246,0.0001021904,0.00004893495,0.000104797,0.000003470895,0.00005686193],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07587615,"threshold_uncertainty_score":0.6660598,"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."}}