{"id":"W3049044764","doi":"10.17072/2218-9173-2018-3-489-501","title":"RURAL TERRITORIES DEVELOPMENT THROUGH THE GOVERMENT SUPPORT OF BIOENERGY","year":2018,"lang":"ru","type":"article","venue":"ARS ADMINISTRANDI (Искусство управления)","topic":"Digitalization and Economic Development in Agriculture","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Bioenergy; Sustainable development; Renewable energy; Business; Rural area; Environmental planning; Economic growth; Natural resource economics; Environmental resource management; Economics; Political science; Geography; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004837696,0.0007299879,0.0007077153,0.0001342951,0.0007539722,0.0009670866,0.001071273,0.0002715467,0.006142378],"category_scores_gemma":[0.00008930974,0.0005243497,0.0002742735,0.000720608,0.0007655055,0.001720808,0.0004880047,0.0002072907,0.001866686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001623381,"about_ca_system_score_gemma":0.000421866,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002532498,"about_ca_topic_score_gemma":0.0006512017,"domain_scores_codex":[0.996072,0.00002864298,0.001632774,0.0006530493,0.0006982819,0.0009152425],"domain_scores_gemma":[0.9976994,0.00006696495,0.001104052,0.0006228831,0.0004320783,0.00007464254],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000691004,0.001630329,0.04813093,0.001177827,0.001561325,0.00005428862,0.009944853,0.0000267677,0.0001940785,0.1560691,0.7663218,0.01419761],"study_design_scores_gemma":[0.001288727,0.0001423048,0.01131397,0.0002420793,0.0001432214,0.00001726058,0.003685054,0.00002077515,0.001920019,0.001356287,0.9790958,0.0007745397],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.378458,0.0005001442,0.0003647998,0.01292067,0.01357671,0.00165118,0.0002339385,0.000324974,0.5919696],"genre_scores_gemma":[0.9681899,0.0001876751,0.0004512397,0.004511292,0.001908669,0.00005604051,0.0007479481,0.00007205998,0.02387518],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5897319,"threshold_uncertainty_score":0.9997208,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01563707338944092,"score_gpt":0.2242255862992495,"score_spread":0.2085885129098086,"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."}}