{"id":"W4405303321","doi":"10.25683/volbi.2019.49.444","title":"ПЕРСПЕКТИВЫ РАЗВИТИЯ ТОРГОВЫХ ЦЕНТРОВ В РОССИЙСКОЙ ФЕДЕРАЦИИ","year":2019,"lang":"ru","type":"article","venue":"Бизнес, образование, право","topic":"Regional Socio-Economic Development Trends","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Distribution (mathematics); Christian ministry; Gross domestic product; Population; External trade; Product (mathematics); Russian federation; Business; Retail trade; Economics; Economy; Geography; International trade; Regional science; Economic growth; Commerce; Political science","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","sts","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","insufficient_payload"],"category_scores_codex":[0.002778545,0.001432474,0.001796135,0.00060053,0.001643972,0.0008705297,0.002965462,0.001437301,0.03645141],"category_scores_gemma":[0.0003325957,0.001537244,0.001084347,0.00171045,0.00142875,0.001634197,0.0009069295,0.00148417,0.05418245],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002131666,"about_ca_system_score_gemma":0.00234541,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003531472,"about_ca_topic_score_gemma":0.001290906,"domain_scores_codex":[0.9894759,0.0008604538,0.001925575,0.002440243,0.002211768,0.003086081],"domain_scores_gemma":[0.9944028,0.001028372,0.001102641,0.001792892,0.0003910773,0.001282217],"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":[0.000544896,0.001760272,0.1837052,0.000653218,0.0020689,0.0002890819,0.06296253,0.0003279491,0.001607444,0.1568827,0.4360696,0.1531283],"study_design_scores_gemma":[0.002824521,0.0002956558,0.06035898,0.0003727408,0.0001832094,0.00002487796,0.01149036,0.0002623545,0.000329661,0.006544375,0.9148656,0.00244767],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4613016,0.002079951,0.00006532908,0.01643181,0.01050716,0.001622512,0.000137376,0.0006012789,0.5072531],"genre_scores_gemma":[0.7330142,0.001798472,0.0008543992,0.002342548,0.002293525,0.00009957937,0.000155542,0.0002187471,0.259223],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.478796,"threshold_uncertainty_score":0.999859,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01759140962543337,"score_gpt":0.2755214973953609,"score_spread":0.2579300877699275,"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."}}