{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004050756,0.0001144441,0.00008319355,0.0002360735,0.000510211,0.001148979,0.000233604,0.0002415324,0.01066688],"category_scores_gemma":[0.0006670582,0.00005433334,0.0001196068,0.0004520781,0.0004768708,0.0004766728,0.001258403,0.0003935677,0.001625287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009428742,"about_ca_system_score_gemma":0.003373238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00592723,"about_ca_topic_score_gemma":0.01115624,"domain_scores_codex":[0.9995903,0.0001421483,0.00001752953,0.0000447786,0.0000984613,0.0001068443],"domain_scores_gemma":[0.9996759,0.00006660407,0.00007262384,0.00004637879,0.0000659931,0.00007255262],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008243878,0.0001284539,0.03124396,0.0006102332,0.000056283,0.001270021,0.004004853,0.002027708,0.004624751,0.7029555,0.02707745,0.2259183],"study_design_scores_gemma":[0.000008595058,0.00006094509,0.03819773,0.0001328044,0.00001268396,0.0004530448,0.001657341,0.0005274555,0.001378314,0.01164852,0.9459116,0.00001091504],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.197479,0.004541078,0.003586747,0.008976093,0.0002450173,0.00007508443,0.0009427856,0.0001192852,0.7840348],"genre_scores_gemma":[0.8807782,0.003761945,0.00185824,0.000313678,0.00004593184,0.00003729587,0.0006364489,0.00002591803,0.1125423],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01066688,"threshold_uncertainty_score":0.03568429,"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."}}