{"id":"W7000005955","doi":"","title":"Economic Impact of the Michigan Large Special Event Fund","year":2018,"lang":"en","type":"article","venue":"Upjohn Research (W.E. Upjohn Institute for Employment Research)","topic":"Sport and Mega-Event Impacts","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economic impact analysis; Revenue; Convention; Work (physics); State (computer science); Visitor pattern; Authorization; Scope (computer science); Commission; Quarter (Canadian coin)","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","insufficient_payload"],"consensus_categories":["sts"],"category_scores_codex":[0.01773581,0.0003574139,0.0005382902,0.001068374,0.004538991,0.0004106202,0.002687287,0.0003314482,0.003484345],"category_scores_gemma":[0.002254304,0.0002649689,0.0007594442,0.00172516,0.0052057,0.0008756344,0.00104525,0.001121169,0.0006922677],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00272149,"about_ca_system_score_gemma":0.007467269,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03411762,"about_ca_topic_score_gemma":0.1874842,"domain_scores_codex":[0.9902411,0.001205646,0.0007984549,0.0008442889,0.003438676,0.003471817],"domain_scores_gemma":[0.9951391,0.0006952758,0.0002269622,0.001305736,0.001608888,0.00102402],"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":[0.001382796,0.001289773,0.02166699,0.0001145869,0.0005674182,0.0000223912,0.02058325,0.0001261479,0.001754904,0.4383771,0.506122,0.007992688],"study_design_scores_gemma":[0.001434638,0.001278704,0.01368425,0.0001591858,0.00001806057,0.000003241193,0.001163797,0.00006214449,0.002801019,0.005950487,0.9731461,0.0002983599],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9197724,0.0001638634,0.00006247853,0.002848368,0.002432702,0.003874092,0.0004041517,0.00007281726,0.07036909],"genre_scores_gemma":[0.9716035,0.0003884284,0.0000751545,0.00005390594,0.007852704,0.0002156512,0.00008102525,0.00007261123,0.01965702],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4670241,"threshold_uncertainty_score":0.9999803,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2485348724330402,"score_gpt":0.5323308454125963,"score_spread":0.2837959729795562,"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."}}