{"id":"W3085763712","doi":"","title":"IDENTIFIKASI HAMA PADA TANAMAN KEDELAI DENGAN MENGGUNAKAN METODE FUZZY","year":2018,"lang":"id","type":"article","venue":"","topic":"Agricultural Development and Management","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Mathematics; Physics","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":["sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0006220283,0.0006405993,0.000513683,0.00004800057,0.001324912,0.0007025838,0.001027841,0.0002934408,0.008293086],"category_scores_gemma":[0.00005939346,0.000236967,0.0003042565,0.00102266,0.0003441437,0.0005754762,0.0007297592,0.0002709945,0.006376284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001466513,"about_ca_system_score_gemma":0.0000232433,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001110753,"about_ca_topic_score_gemma":0.008509788,"domain_scores_codex":[0.9960232,0.0002034099,0.0007443682,0.001073796,0.0008020515,0.001153172],"domain_scores_gemma":[0.9985988,0.0001052193,0.000277059,0.0002095051,0.0003512276,0.0004581656],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008182089,0.0004942316,0.00654677,0.0000670982,0.0005813669,0.00007318879,0.001232434,6.460103e-7,0.09918431,0.01846055,0.7645923,0.1086852],"study_design_scores_gemma":[0.0003894242,0.0006460022,0.3199228,0.00008619784,0.0001603657,0.00001236606,0.004468,0.00002907743,0.01460801,0.001594575,0.6569302,0.001152976],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8060945,0.0003495113,0.00002800199,0.01200753,0.002592399,0.0009451697,0.00002157971,0.0003637934,0.1775976],"genre_scores_gemma":[0.7342491,0.0003012366,0.0003557005,0.001295187,0.001956461,0.00002862323,0.0001444767,0.000004330206,0.2616648],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.313376,"threshold_uncertainty_score":0.9999752,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0198375570046961,"score_gpt":0.2208285860140855,"score_spread":0.2009910290093894,"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."}}