{"id":"W2947672902","doi":"10.5539/jas.v11n8p31","title":"Stochastic Meta Frontier Analysis of Smallholder Rice Farmers’ Technical Efficiency","year":2019,"lang":"en","type":"article","venue":"Journal of Agricultural Science","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Priority Academic Program Development of Jiangsu Higher Education Institutions; Nanjing Agricultural University","keywords":"Inefficiency; Production (economics); Stochastic frontier analysis; Manure; Agricultural science; Food security; Rice farming; Agricultural economics; Frontier; Economics; Business; Production–possibility frontier; Agronomy; Environmental science; Agriculture; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.01081747,0.0002586854,0.001435255,0.002305149,0.0002471331,0.0003548396,0.003764754,0.00009749414,0.0006515363],"category_scores_gemma":[0.004350996,0.0001176906,0.001525037,0.02355635,0.000832354,0.001242479,0.0003220481,0.0003906888,0.0001106819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001703223,"about_ca_system_score_gemma":0.0002903492,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003559486,"about_ca_topic_score_gemma":0.00001531706,"domain_scores_codex":[0.9902707,0.0002262806,0.001995893,0.0006704677,0.006300185,0.0005364803],"domain_scores_gemma":[0.9919436,0.001192072,0.002407032,0.0007199425,0.003426405,0.0003109355],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00004482404,0.0005453281,0.01178948,0.000006040095,0.001871475,0.0000102643,0.0008472143,0.4163036,0.5650266,0.0007475188,0.001635198,0.00117246],"study_design_scores_gemma":[0.000387861,0.0004223384,0.9754089,0.00002742062,0.008084988,0.0001133635,0.002351398,0.009671343,0.002583679,0.0003358992,0.0002034954,0.0004093263],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9778704,0.0005008722,0.01877595,0.0007159138,0.000530139,0.0001411854,0.000007871576,0.00001175796,0.001445881],"genre_scores_gemma":[0.9965456,0.000006182186,0.002561784,0.00008297196,0.00004535321,9.632269e-7,5.79527e-7,0.000004030039,0.000752529],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9636194,"threshold_uncertainty_score":0.9971984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04846699833554079,"score_gpt":0.3352620700296063,"score_spread":0.2867950716940655,"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."}}