{"id":"W6976765820","doi":"10.6068/dp14ba86ec77943","title":"Trend 1997 - 2005. Statistics Canada. CANSIM: Business, Consumer and Property Services - Arts, Entertainment and Recreation | 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: 075-001-010.","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; Entertainment; Amusement; Census; Socioeconomic status; Descriptive statistics; Tourism","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":[0.001960922,0.00243583,0.002587363,0.009188631,0.003359956,0.005053574,0.005166356,0.001476564,0.08997206],"category_scores_gemma":[0.01773719,0.001707406,0.001956252,0.04468785,0.0006946467,0.002633823,0.002189083,0.003202745,0.05580368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04940674,"about_ca_system_score_gemma":0.1465358,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9949118,"about_ca_topic_score_gemma":0.9930726,"domain_scores_codex":[0.9955822,0.0002447862,0.0004826376,0.0005849112,0.002073125,0.001032265],"domain_scores_gemma":[0.9681709,0.001175359,0.0009346753,0.0008760154,0.02738607,0.00145703],"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":[0.0000178005,0.000005247239,0.0008351065,0.0001996463,0.00001653346,0.000006278332,0.00001834646,0.00009310334,0.000007865982,0.0003540865,0.9971516,0.001294521],"study_design_scores_gemma":[0.0001177553,0.000009927267,0.01927649,0.0008077492,0.00006520923,0.0000252405,0.0004775186,0.0004296288,0.0001639992,0.0006058243,0.9779483,0.0000724061],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004857686,0.00004974519,0.00002236259,0.0001213304,0.00002643381,0.00001145076,0.9988031,0.00005384111,0.0008631608],"genre_scores_gemma":[0.0007587583,0.0002839308,0.0003119989,0.0001411961,0.00001720871,0.00009241034,0.9942485,0.0001042216,0.004041724],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08997206,"threshold_uncertainty_score":0.3584727,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02333470182269011,"score_gpt":0.2451866410350607,"score_spread":0.2218519392123706,"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."}}