{"id":"W4387216938","doi":"10.59697/jik.v4i2.337","title":"SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN LAHAN PERTANIAN YANG TEPAT UNTUK MENINGKATKAN HASIL PANEN CABAI MENGGUNAKAN METODE MOORA","year":2020,"lang":"en","type":"article","venue":"Jurnal Informatika Kaputama (JIK)","topic":"Decision Support System Applications","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Selection (genetic algorithm); Mathematics; Correctness; Ranking (information retrieval); Horticulture; Agricultural engineering; Mathematical optimization; Computer science; Algorithm; Engineering; Artificial intelligence; Biology","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":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001022652,0.0007776066,0.0009979683,0.0006387394,0.0009774551,0.002177161,0.001419331,0.0002860604,0.003411829],"category_scores_gemma":[0.0002947014,0.0007074366,0.0004604602,0.001730479,0.000113612,0.00578972,0.00076484,0.0006868131,0.009560925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002199555,"about_ca_system_score_gemma":0.0001621928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004579565,"about_ca_topic_score_gemma":0.0001270491,"domain_scores_codex":[0.9945637,0.00004898175,0.002098803,0.0006895201,0.001565704,0.001033299],"domain_scores_gemma":[0.9967098,0.0001505004,0.001349489,0.000919819,0.0005753507,0.0002950174],"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":[0.0007103888,0.0006816779,0.04174542,0.003272998,0.001315122,0.0005165766,0.01992883,0.000888239,0.007616005,0.03141482,0.8036757,0.08823425],"study_design_scores_gemma":[0.001505989,0.00006219079,0.004551998,0.0001936997,0.0002370999,0.00009631171,0.006322603,0.01837744,0.0002823392,0.0002604302,0.9670326,0.001077297],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2856739,0.0003368157,0.005277504,0.01762871,0.001374724,0.002739546,0.0001420856,0.001807602,0.6850191],"genre_scores_gemma":[0.9842787,0.00001461641,0.001134175,0.007795875,0.002234558,0.0001714391,0.0003332286,0.0001371252,0.003900219],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6986049,"threshold_uncertainty_score":0.9995376,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04063850811124614,"score_gpt":0.2312003517783173,"score_spread":0.1905618436670711,"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."}}