{"id":"W6957974123","doi":"10.6068/dp14ba812797a86","title":"Trend 1997 - 2005. Statistics Canada. CANSIM: Culture and Leisure - Sports | Country: Canada | Table: Summary statistics for arts, entertainment and recreation | Variable: Fitness and recreational sports centres, Operating expenses | 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; Attendance; Socioeconomic status; Population; Economic statistics; Population statistics","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":[0.0022525,0.002222383,0.002521262,0.008342869,0.003286714,0.004701399,0.004714136,0.00132121,0.1065006],"category_scores_gemma":[0.01644977,0.001767854,0.002005374,0.03887409,0.0006462935,0.002526936,0.002156405,0.003063816,0.0567276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06112598,"about_ca_system_score_gemma":0.1687279,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9958665,"about_ca_topic_score_gemma":0.9935254,"domain_scores_codex":[0.9953533,0.0002994091,0.000471513,0.0005472052,0.002264774,0.001063792],"domain_scores_gemma":[0.9658654,0.001116256,0.0009169084,0.0008689182,0.0295905,0.001641979],"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":[0.00002371304,0.000006782092,0.0009796427,0.0002399905,0.00001923983,0.00000693343,0.00002275688,0.0001000902,0.000009246341,0.0004251366,0.9959581,0.002208286],"study_design_scores_gemma":[0.0001158607,0.00001338443,0.02382201,0.0008788208,0.00007027175,0.00002787252,0.0005313969,0.0004541035,0.0001618705,0.0006247414,0.9732218,0.0000778699],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007277263,0.00008059591,0.00004189859,0.0001923462,0.00004538862,0.0000229275,0.9976919,0.00008556487,0.001766741],"genre_scores_gemma":[0.001454748,0.0005392188,0.0006982959,0.0002662268,0.00002755355,0.0001730719,0.987192,0.0001904812,0.009458338],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1065006,"threshold_uncertainty_score":0.4435021,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02126495477596345,"score_gpt":0.2507634550618053,"score_spread":0.2294985002858418,"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."}}