{"id":"W4400989907","doi":"10.69554/pmpv2557","title":"An evaluation of Churchill Downs’ tax increment financing district","year":2022,"lang":"en","type":"article","venue":"Journal of urban regeneration and renewal","topic":"demographic modeling and climate adaptation","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economics; Finance; Business","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":[],"consensus_categories":[],"category_scores_codex":[0.008748665,0.00007447983,0.0001941855,0.0003757031,0.0002765905,0.00008384932,0.0001988161,0.00002904078,0.0001689764],"category_scores_gemma":[0.0003615907,0.00005459089,0.00008902878,0.0004208768,0.00003026549,0.0002515757,0.00003331699,0.0001125858,4.692318e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005850685,"about_ca_system_score_gemma":0.0001842096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003761965,"about_ca_topic_score_gemma":0.00003378665,"domain_scores_codex":[0.9959251,0.0006367018,0.0008690887,0.0001611361,0.002320298,0.00008767061],"domain_scores_gemma":[0.9978951,0.00009085568,0.0009252538,0.000188934,0.0008241163,0.00007571845],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002873693,0.0004281394,0.01620043,0.000008974374,0.00006465902,0.000008339302,0.004234783,0.5605667,0.1110954,0.003756052,0.01176584,0.2915832],"study_design_scores_gemma":[0.003578193,0.002211914,0.04152821,0.00004058455,0.0002627312,0.0002459114,0.006187428,0.9079666,0.008081337,0.02064326,0.008919703,0.0003341392],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9861637,0.001011413,0.01144914,0.0005721961,0.0004280643,0.00008668653,0.00001438365,0.000003491062,0.0002709523],"genre_scores_gemma":[0.998574,0.00008870246,0.0009108619,0.00005929829,0.0001542127,0.000004011303,0.00001387775,0.00000450293,0.0001905691],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3473999,"threshold_uncertainty_score":0.303213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1100375547363284,"score_gpt":0.3595862696898319,"score_spread":0.2495487149535035,"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."}}