{"id":"W2612148603","doi":"10.29244/fagb.7.2.103-120","title":"ANALISIS EFISIENSI TEKNIS USAHATANI PADI DI JAWA DAN LUAR JAWA : PENDEKATAN DATA ENVELOPMENT ANALYSIS (DEA)","year":2017,"lang":"en","type":"article","venue":"Forum Agribisnis","topic":"Agricultural Development and Management","field":"Agricultural and Biological Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Encana (Canada)","funders":"","keywords":"Data envelopment analysis; Agricultural science; Tobit model; Agriculture; Production (economics); Fertilizer; Mathematics; Business; Agricultural economics; Economics; Statistics; Geography; Environmental science; Agronomy","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":[],"category_scores_codex":[0.0005882456,0.0005284678,0.0006367525,0.00006621981,0.002214771,0.0009178308,0.003193428,0.0001878612,0.0009204868],"category_scores_gemma":[0.000107063,0.0002046913,0.0002920192,0.0007406279,0.0001546345,0.001153353,0.00267168,0.0002151403,0.0001887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001198868,"about_ca_system_score_gemma":0.00002141571,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002489669,"about_ca_topic_score_gemma":0.01605143,"domain_scores_codex":[0.9960737,0.00008993421,0.0006250187,0.00132663,0.0008638571,0.00102092],"domain_scores_gemma":[0.9978623,0.00009653619,0.0005173353,0.00102292,0.0001408649,0.0003600022],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007751818,0.0003436471,0.6313558,0.00002245389,0.001933853,0.0001141927,0.0002373139,0.00001518941,0.009627981,0.001507437,0.1387479,0.2160168],"study_design_scores_gemma":[0.0001786254,0.0001111754,0.7947744,0.00001811406,0.0003581274,0.000004157727,0.001184998,0.0001397198,0.0006386272,0.00006278964,0.2019627,0.000566507],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9689775,0.0001572008,0.00005590352,0.01369013,0.0004810771,0.0006708305,0.0005924155,0.00022285,0.01515214],"genre_scores_gemma":[0.9909336,0.0004297242,0.0003008022,0.0005392272,0.0002745373,0.00003791734,0.004658941,0.000003859916,0.002821403],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2154503,"threshold_uncertainty_score":0.9999928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04646094977294685,"score_gpt":0.2534135224801395,"score_spread":0.2069525727071927,"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."}}