{"id":"W2557492388","doi":"","title":"Comparing The Potential For Creative Clusters For Urban Regeneration","year":2015,"lang":"en","type":"article","venue":"QSpace (Queen's University Library)","topic":"Cultural Industries and Urban Development","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Regeneration (biology); Computer science; Geography; Biology; Cell biology","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":[0.002677588,0.0002434746,0.0002042242,0.001884625,0.003363438,0.004442365,0.0009323873,0.000526729,0.009713328],"category_scores_gemma":[0.006716936,0.0001301963,0.0003589853,0.001803232,0.004623025,0.00164038,0.005823926,0.0004944375,0.0003473539],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01412318,"about_ca_system_score_gemma":0.006671623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09555545,"about_ca_topic_score_gemma":0.3542152,"domain_scores_codex":[0.9968361,0.001332999,0.0000836019,0.0001542117,0.0007122547,0.0008807509],"domain_scores_gemma":[0.9958359,0.001598407,0.0003606419,0.0003585215,0.0006293512,0.001217166],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.004977556,0.0007933524,0.4263454,0.001197941,0.0003407501,0.001486603,0.158562,0.006279476,0.003007247,0.1826825,0.009074179,0.2052531],"study_design_scores_gemma":[0.0002060511,0.0007413686,0.6644107,0.0002999757,0.0001819828,0.0002572236,0.2821999,0.001863459,0.00115574,0.009105858,0.03952614,0.00005161659],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9256036,0.0003252615,0.0003070925,0.0006354942,0.00001386923,0.00009376607,0.0001366378,0.000008410592,0.072876],"genre_scores_gemma":[0.9979273,0.0001166045,0.0002084521,0.00001673113,0.0000030184,0.00002896019,0.00004921242,0.000002821376,0.001646969],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09555545,"threshold_uncertainty_score":0.1899985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03745465494486733,"score_gpt":0.2333691489512267,"score_spread":0.1959144940063594,"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."}}