{"id":"W20675752","doi":"10.1302/0301-620x.92b8.23980","title":"Совершенствование муниципально-территориального устройства Воронежской области как предпосылка устойчивого социально-экономического развития региона","year":2013,"lang":"en","type":"article","venue":"Tambov University Reports Series Natural and Technical Sciences","topic":"Regional Economic Development and Innovation","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Local government; Government (linguistics); Regional science; Business; Sustainable development; Environmental planning; Geography; Political science; Public administration","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":[0.001334124,0.0002637518,0.0004228244,0.001850498,0.0006433124,0.002530123,0.0004880311,0.0007531863,0.00776771],"category_scores_gemma":[0.004193212,0.000511418,0.0004057633,0.001801467,0.001959859,0.0009674417,0.0007448189,0.0008869045,0.002942818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007761812,"about_ca_system_score_gemma":0.002059628,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002987576,"about_ca_topic_score_gemma":0.005410956,"domain_scores_codex":[0.9988326,0.0002685186,0.00008392263,0.0001531401,0.0005430508,0.0001186716],"domain_scores_gemma":[0.9980949,0.0007466716,0.000465024,0.0002063301,0.0003674232,0.0001197181],"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":[0.0003455186,0.0002320824,0.01768706,0.001007259,0.00007833055,0.001914382,0.00166109,0.003079463,0.0674738,0.09488478,0.005047191,0.8065889],"study_design_scores_gemma":[0.0003106776,0.001007421,0.07800081,0.001000353,0.0003467707,0.01584629,0.003462801,0.006285704,0.09388458,0.1243522,0.6750462,0.0004562073],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4236009,0.145271,0.18566,0.00984271,0.001885649,0.00059703,0.001054016,0.0004798277,0.2316089],"genre_scores_gemma":[0.7803155,0.04676282,0.1492552,0.0005071441,0.0005216666,0.0005685673,0.0003183475,0.0001744063,0.02157647],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00776771,"threshold_uncertainty_score":0.0259856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009332816896104384,"score_gpt":0.1703498734295191,"score_spread":0.1610170565334147,"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."}}