{"id":"W2576533638","doi":"10.15405/epsbs.2017.01.30","title":"The Urban Regeneration to Increase Well-Being of Older People: “Museum Quarter” Project in Tomsk","year":2017,"lang":"en","type":"article","venue":"The European Proceedings of Social & Behavioural Sciences","topic":"Cultural Industries and Urban Development","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Attractiveness; Urban regeneration; Government (linguistics); General partnership; Business; Investment (military); Process (computing); Post-industrial society; Public relations; Environmental planning; Marketing; Political science; Computer science; Geography; Finance; Psychology; Politics","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.003527625,0.0001482217,0.0001985005,0.00007037082,0.005178036,0.0007860263,0.001484341,0.00006049794,0.00002066688],"category_scores_gemma":[0.0001879277,0.00008999144,0.00008396736,0.0005721,0.001257986,0.0006131071,0.0002513478,0.0001757094,0.000005887211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001005295,"about_ca_system_score_gemma":0.0001707259,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01821368,"about_ca_topic_score_gemma":0.01734812,"domain_scores_codex":[0.9979596,0.00009689597,0.000438303,0.000295185,0.0007601579,0.0004498339],"domain_scores_gemma":[0.9989517,0.00005100009,0.0005119254,0.00009867983,0.0003065351,0.00008018711],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005363235,0.0001280935,0.596233,0.00001875646,0.00001684057,0.000002818871,0.2577589,0.000001861087,0.0036453,0.02090751,0.1045648,0.01666854],"study_design_scores_gemma":[0.0002722251,0.0001357136,0.9012337,0.00009224363,0.00002648313,0.000001284605,0.07622951,0.00001262455,0.0007719101,0.0002847571,0.02066691,0.0002726539],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9204172,0.000021355,6.620035e-7,0.01100428,0.0002170395,0.0005319297,0.000002153834,0.00002253093,0.06778283],"genre_scores_gemma":[0.9939105,0.00001995125,0.00005096224,0.00005380623,0.000257796,0.00001969786,8.075003e-7,0.000008771375,0.005677717],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3050008,"threshold_uncertainty_score":0.9961171,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03607707407730362,"score_gpt":0.3038023846790179,"score_spread":0.2677253106017142,"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."}}