{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008100893,0.0008425239,0.000769208,0.001294219,0.0007400805,0.002525661,0.0007226191,0.001075887,0.004463847],"category_scores_gemma":[0.001779549,0.0004078471,0.0009692443,0.0009471338,0.0005323386,0.00156109,0.0006983891,0.0008404272,0.001196195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000944328,"about_ca_system_score_gemma":0.001227529,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007050013,"about_ca_topic_score_gemma":0.00639212,"domain_scores_codex":[0.9993505,0.00009205761,0.00005952394,0.0001767805,0.0002691849,0.00005187954],"domain_scores_gemma":[0.9993222,0.0002450679,0.0000549824,0.0000438577,0.0003096627,0.00002427723],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006554627,0.0002633547,0.01719353,0.001596568,0.000307114,0.000826788,0.001381136,0.1383227,0.1312191,0.02948339,0.005377186,0.6733738],"study_design_scores_gemma":[0.00005082894,0.0003166329,0.01300419,0.0002985628,0.000278258,0.001016364,0.001809013,0.8707447,0.05347054,0.02959111,0.02928132,0.0001384631],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1023366,0.002702332,0.8697314,0.0006977149,0.0001910478,0.0002325815,0.0005754675,0.0008376276,0.02269522],"genre_scores_gemma":[0.6465685,0.002220763,0.3301823,0.0002104001,0.00007463705,0.0002787626,0.0007780393,0.0001057116,0.01958088],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007050013,"threshold_uncertainty_score":0.01493305,"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."}}