{"id":"W2110543931","doi":"10.5539/ass.v11n3p91","title":"An Analysis of Technical Efficiency of Rice Production in Indonesia","year":2014,"lang":"en","type":"article","venue":"Asian Social Science","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Inefficiency; Production (economics); Incentive; Agricultural economics; Agriculture; Work (physics); Stochastic frontier analysis; Economics; Production–possibility frontier; Business; Agricultural science; Geography; Microeconomics; Environmental science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001151179,0.0002872194,0.0003782823,0.001473511,0.0001724579,0.0008454786,0.0003184258,0.0001582175,0.000648904],"category_scores_gemma":[0.002679071,0.000190869,0.0005537413,0.001780227,0.0003532766,0.0004361369,0.0003535011,0.0002111533,0.0001119393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001961397,"about_ca_system_score_gemma":0.0009832076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02151664,"about_ca_topic_score_gemma":0.01875723,"domain_scores_codex":[0.999265,0.0002250641,0.00006334171,0.0001184024,0.0002198266,0.000108329],"domain_scores_gemma":[0.9983676,0.0008941605,0.0003576502,0.0001164874,0.0002150147,0.0000490419],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002578915,0.0002408176,0.7492437,0.0001445715,0.0002613404,0.0005084197,0.0003757381,0.2063335,0.004180175,0.002913545,0.000320067,0.03522015],"study_design_scores_gemma":[0.00001178196,0.0001289307,0.8301421,0.00001910773,0.00004892707,0.0001720739,0.0006295408,0.1641625,0.002462105,0.001246343,0.0009526597,0.00002380579],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995142,0.00008144697,0.002533881,0.00002702455,8.548766e-7,0.00001251794,0.0002704155,0.000009981428,0.001921942],"genre_scores_gemma":[0.9984669,0.00004386231,0.0009256708,0.000002425572,6.733894e-7,0.000008125015,0.0002385786,0.000002469497,0.0003112483],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02151664,"threshold_uncertainty_score":0.04278284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03018998889943069,"score_gpt":0.3773924099283194,"score_spread":0.3472024210288887,"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."}}