{"id":"W2021622266","doi":"10.2135/cropsci2014.02.0113","title":"Genotypic Association of Parameters Commonly Used to Predict Canning Quality of Dry Bean","year":2014,"lang":"en","type":"article","venue":"Crop Science","topic":"Plant pathogens and resistance mechanisms","field":"Agricultural and Biological Sciences","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Lethbridge College; Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada","keywords":"Phaseolus; Dry bean; Biology; Selection (genetic algorithm); Breeding program; Genotype; Genetic variation; Coefficient of variation; Gene–environment interaction; Biotechnology; Agronomy; Cultivar; Statistics; Mathematics; Genetics; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001774049,0.00006122469,0.0001683649,0.00001813452,0.0001637934,0.00002554796,0.0003584809,0.00004052203,0.00001207109],"category_scores_gemma":[0.0004061204,0.00002478664,0.00004477193,0.0005138619,0.0001203249,0.00007484205,0.00005956175,0.00004306111,0.000003217772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004200637,"about_ca_system_score_gemma":0.00001942247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004431158,"about_ca_topic_score_gemma":0.001700704,"domain_scores_codex":[0.998841,0.0000798951,0.0002278608,0.0001986794,0.0004367725,0.0002157376],"domain_scores_gemma":[0.9993115,0.0001921393,0.0002186166,0.0000667908,0.0001226945,0.00008825809],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000007522436,0.00001830327,0.07417614,0.000004708693,0.000001519481,1.033299e-7,0.0001226117,0.00005098201,0.9213399,0.0003769924,0.0000181267,0.003883103],"study_design_scores_gemma":[0.00005485614,0.0001648889,0.8436928,0.00002371936,0.00000399266,1.293973e-7,0.0001074181,0.0002470956,0.1550651,0.0002237202,0.000336901,0.00007936242],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989505,0.00001006357,0.0002346387,0.0001854713,0.0001198032,0.00009088183,0.00006850452,0.00001436113,0.0003258073],"genre_scores_gemma":[0.9989595,0.000001384423,0.0008503289,0.00006183828,0.00002153469,0.000002005479,0.000004452825,3.140286e-7,0.00009867063],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7695166,"threshold_uncertainty_score":0.1259783,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03495714933522486,"score_gpt":0.2539414961963904,"score_spread":0.2189843468611655,"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."}}