{"id":"W6901655773","doi":"10.6068/dp14ba8c5ec9590","title":"Most Recent Data (2008). Statistics Canada. CANSIM: Business, Consumer and Property Services - Arts, Entertainment and Recreation | Country: Canada | Table: Spectator sports, event promoters, artists and related industries, operating expenses, by North American Industry Classification System (NAICS) | Variable: Insurance, Agents and managers for artists, athletes, entertainers and other public figures | Units: %, 2008. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-010.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Recreation; Census; Amusement; Entertainment; Event (particle physics); Official statistics; Tourism; Descriptive statistics; Socioeconomic status","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"],"consensus_categories":[],"category_scores_codex":[0.0009153003,0.001129781,0.001273556,0.0001744596,0.000405352,0.0009742448,0.001038584,0.0005428071,0.0001984649],"category_scores_gemma":[0.0003324509,0.0009881194,1.565529e-7,0.0008326279,0.0006613907,0.0008295471,0.0009340937,0.0008994372,0.00000268322],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005677262,"about_ca_system_score_gemma":0.007879884,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9951028,"about_ca_topic_score_gemma":0.9856139,"domain_scores_codex":[0.9935067,0.0005311479,0.001412964,0.0023956,0.001176213,0.0009773421],"domain_scores_gemma":[0.9940252,0.0003097719,0.001769774,0.00249103,0.0004316,0.000972637],"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":[0.0002100358,0.00009977806,0.00865294,0.002248788,0.0006299982,0.0002090851,0.0000113664,0.000003419461,0.000006833761,0.00005683654,0.986378,0.001492901],"study_design_scores_gemma":[0.00171902,0.00008017201,0.0006612288,0.0004658279,0.0005546821,0.0003468672,0.001496639,0.007828591,5.015264e-8,3.83831e-8,0.9857366,0.001110282],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001192469,0.007761077,0.00000723552,0.00002823375,0.0002722433,0.003186672,0.9883285,0.0001039748,0.0001928844],"genre_scores_gemma":[0.0005836756,0.005715615,0.0002752217,0.0003029079,0.0000806073,0.0001187984,0.9917647,0.0004023378,0.0007561056],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.009488917,"threshold_uncertainty_score":0.9992569,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02962813475175321,"score_gpt":0.2422260848926842,"score_spread":0.212597950140931,"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."}}