{"id":"W6901792862","doi":"10.6068/dp14ba7f93f6431","title":"Trend 1997 - 2005. Statistics Canada. CANSIM: Culture and Leisure - Sports | Country: Canada | Table: Summary statistics for arts, entertainment and recreation | Variable: Spectator sports, Salaries, wages and benefits | Units: $CAD x 1,000,000, 1997-2005. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-053.","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; Descriptive statistics; Census; Economic statistics; Official statistics; Socioeconomic status; Attendance; Population; Population statistics; Entertainment","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":[0.002333406,0.002291352,0.002585631,0.008649704,0.003391301,0.004717059,0.004847955,0.001332463,0.1021109],"category_scores_gemma":[0.01635347,0.001761123,0.002080384,0.03976757,0.0006504284,0.002514201,0.002162668,0.003096182,0.05545876],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06108972,"about_ca_system_score_gemma":0.1670424,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9959128,"about_ca_topic_score_gemma":0.9935203,"domain_scores_codex":[0.9953126,0.0002995379,0.0004765368,0.000541342,0.002285893,0.001084099],"domain_scores_gemma":[0.965071,0.001065472,0.0009183621,0.0008880984,0.03041333,0.001643732],"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":[0.00002667368,0.000007240008,0.001050342,0.0002660158,0.00002175111,0.000007370057,0.00002367504,0.0001041014,0.00001060652,0.0004330235,0.9956242,0.002425086],"study_design_scores_gemma":[0.000122564,0.00001421177,0.02492841,0.0008999963,0.00007643682,0.00002856698,0.0005211952,0.0004579526,0.0001730463,0.000642045,0.9720528,0.00008276173],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007450984,0.00008665272,0.0000440318,0.0001881971,0.00004656614,0.00002349638,0.9977407,0.00008958918,0.001706174],"genre_scores_gemma":[0.001459563,0.000569175,0.0007260581,0.0002672856,0.00002750099,0.0001747703,0.9876176,0.0001931217,0.008964974],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1021109,"threshold_uncertainty_score":0.443239,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0182357014734167,"score_gpt":0.2350338996164631,"score_spread":0.2167981981430464,"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."}}