{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005663119,0.0009964629,0.001443428,0.003542044,0.0004847033,0.003179966,0.0003974265,0.0006093755,0.004361204],"category_scores_gemma":[0.01092873,0.0003675258,0.001712291,0.006555682,0.0004215233,0.001676736,0.0009100023,0.0009183415,0.0008947861],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001170797,"about_ca_system_score_gemma":0.00193202,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006800829,"about_ca_topic_score_gemma":0.003644608,"domain_scores_codex":[0.9967135,0.0008397335,0.0003872504,0.0003474414,0.001470992,0.000241127],"domain_scores_gemma":[0.9919396,0.005325565,0.0006026328,0.0004306882,0.001626809,0.00007472072],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0009567906,0.0006949127,0.1183448,0.003610055,0.00134019,0.0009493408,0.002645482,0.3621202,0.01898005,0.02051447,0.006645219,0.4631985],"study_design_scores_gemma":[0.0000754432,0.001024247,0.1701991,0.0008219597,0.0006568902,0.0007438438,0.006638186,0.740001,0.0308218,0.01456825,0.03415726,0.000292062],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7060186,0.003343865,0.2669846,0.0007956825,0.0001265778,0.0004630462,0.004945259,0.0006585772,0.01666389],"genre_scores_gemma":[0.9110017,0.002058684,0.07800801,0.00005784883,0.00002258546,0.0004451435,0.003542074,0.0001160965,0.004747733],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006800829,"threshold_uncertainty_score":0.02994978,"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."}}