{"id":"W6976616139","doi":"10.6068/dp14ba8d47c5229","title":"Trend 2007 - 2011. 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: All other expenses, Agents and managers for artists, athletes, entertainers and other public figures | Units: %, 2007-2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-010.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"Immigration and Intercultural Education","field":"Social Sciences","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001575549,0.002651083,0.002810373,0.008584844,0.002598396,0.004833424,0.005404695,0.001585093,0.07739821],"category_scores_gemma":[0.01522009,0.001614887,0.002069458,0.04237713,0.0006717943,0.002574086,0.002015226,0.003419349,0.06148925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03444782,"about_ca_system_score_gemma":0.09597852,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9868664,"about_ca_topic_score_gemma":0.9859986,"domain_scores_codex":[0.9962846,0.0002112955,0.0004124238,0.0005887958,0.001660039,0.0008428446],"domain_scores_gemma":[0.9727656,0.001257451,0.001065673,0.000819938,0.02278976,0.001301524],"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":[0.00001661093,0.000005708211,0.0009130025,0.000162224,0.00001595119,0.000004990737,0.00001119132,0.00009227086,0.000006648794,0.0001977495,0.9977431,0.000830585],"study_design_scores_gemma":[0.0001931358,0.00001198835,0.02373923,0.0008092085,0.00006800376,0.00002685132,0.0004724647,0.0006137267,0.0001859473,0.0005885304,0.9732119,0.00007900506],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005088687,0.00003862025,0.0000142863,0.00008936028,0.00002297745,0.000007459074,0.9992305,0.00004117665,0.0005046656],"genre_scores_gemma":[0.0004436707,0.0001405979,0.0001347765,0.00008511112,0.00001513648,0.00005547404,0.9971389,0.00005305256,0.001933311],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07739821,"threshold_uncertainty_score":0.2589228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03485965626180301,"score_gpt":0.2702019971920144,"score_spread":0.2353423409302114,"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."}}