{"id":"W4372347523","doi":"10.18280/ijsdp.180408","title":"Multi-Criteria Optimization as the Methodology of Ensuring Sustainable Development of Regions: Tula Region of the Russian Federation","year":2023,"lang":"en","type":"article","venue":"International Journal of Sustainable Development and Planning","topic":"Arctic and Russian Policy Studies","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Russian Science Foundation","keywords":"Russian federation; Sustainable development; Environmental planning; Regional science; Environmental resource management; Environmental protection; Business; Political science; Geography; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002260868,0.0000915779,0.0002073505,0.0003067667,0.0007123481,0.00004101381,0.0003142688,0.00006358873,0.000007717987],"category_scores_gemma":[0.001083791,0.00005994464,0.0000542251,0.0003451993,0.0002142808,0.000235635,0.000185184,0.000113253,2.224062e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001560146,"about_ca_system_score_gemma":0.000860705,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003451838,"about_ca_topic_score_gemma":0.00002822867,"domain_scores_codex":[0.9983335,0.0002593671,0.0006312096,0.00009138383,0.0004557717,0.0002287666],"domain_scores_gemma":[0.9980289,0.0003720166,0.0007787761,0.00005838436,0.0007254726,0.00003644676],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.000386794,0.0001038385,0.0182598,0.0003081638,0.0007522975,0.000324927,0.8198313,0.01128431,0.0001734433,0.1431257,0.001738151,0.003711275],"study_design_scores_gemma":[0.0009635589,0.00005131019,0.06708598,0.0006300408,0.00004808699,0.00005803433,0.8893207,0.0006107576,0.004340683,0.006057323,0.03063156,0.0002019134],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9395427,0.0006464788,0.0414724,0.01345072,0.0005912113,0.0004378314,0.000001091029,0.0000172979,0.003840328],"genre_scores_gemma":[0.9764509,0.0001770879,0.01990069,0.00005801686,0.00009051566,0.000005839319,0.000002678357,0.000006737353,0.003307544],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1370683,"threshold_uncertainty_score":0.5478878,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08918730255670712,"score_gpt":0.3707338141326062,"score_spread":0.281546511575899,"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."}}