{"id":"W2351660671","doi":"","title":"Gray Relation Analysis on Yield and Main Agronomic Traits of Rape","year":2011,"lang":"en","type":"article","venue":"Seed","topic":"Medical Research and Treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Gray (unit); Yield (engineering); Relation (database); Mathematics; Computer science; Data mining; Physics; Medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001145569,0.00004187055,0.0001409676,0.0001276399,0.00001320822,0.000001271455,0.00001861394,0.00003758347,0.0002430101],"category_scores_gemma":[0.0001747427,0.00002901495,0.0000470413,0.0001456157,0.00003567309,0.00001582166,0.000006138067,0.00006045548,0.00002189253],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001480824,"about_ca_system_score_gemma":0.00002726502,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001440059,"about_ca_topic_score_gemma":0.00003875234,"domain_scores_codex":[0.9995736,0.00001538459,0.00009362282,0.00009444505,0.0001309825,0.00009190895],"domain_scores_gemma":[0.9996798,0.00006596564,0.00002517771,0.00008297659,0.00001317939,0.000132872],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001798974,0.0007133521,0.9316631,0.0000830401,0.002579876,0.00009309064,0.001526968,0.000001326677,0.0335752,0.001577298,0.0002480156,0.02613978],"study_design_scores_gemma":[0.0007723085,0.0004084735,0.9948856,0.00002394589,0.0002537662,0.000001019266,0.00004288586,0.00009343309,0.003282228,0.0002052019,0.000009845883,0.00002133426],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9898153,0.0000555365,0.0001655325,0.0001230882,0.000008715021,0.0001081405,0.000004669664,0.000006001396,0.00971304],"genre_scores_gemma":[0.998773,0.00003018799,0.00025268,0.00005586249,0.00001122012,0.000003172243,0.0000139546,0.000003168747,0.0008567612],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06322248,"threshold_uncertainty_score":0.266079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04596452904996984,"score_gpt":0.2923442527810461,"score_spread":0.2463797237310763,"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."}}