{"id":"W6939103833","doi":"10.6068/dp14ba8b23d9d89","title":"Trend 2008 - 2010. Statistics Canada. CANSIM: Business, Consumer and Property Services - Arts, Entertainment and Recreation | Country: Canada | Table: Heritage institutions, operating expenses, by North American Industry Classification System (NAICS) | Variable: Advertising, marketing and promotions, Museums (except art museums and galleries) | Units: %, 2008-2010. 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; Entertainment; Amusement; Official statistics; Economic statistics; Socioeconomic status; Descriptive statistics; Per capita","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":[0.001428079,0.002552527,0.002531562,0.009194249,0.002796796,0.0048697,0.005159239,0.001431055,0.07662731],"category_scores_gemma":[0.01560036,0.0014805,0.001806466,0.04321172,0.0006806511,0.002672424,0.00216579,0.002894489,0.06145732],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03568078,"about_ca_system_score_gemma":0.096668,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9885062,"about_ca_topic_score_gemma":0.9877757,"domain_scores_codex":[0.9966967,0.0001760087,0.0003638271,0.0005582607,0.001425629,0.0007795422],"domain_scores_gemma":[0.9734823,0.001157116,0.000917636,0.0008709962,0.02223114,0.001340868],"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":[0.00001504379,0.000004733491,0.0007190766,0.000143477,0.0000130945,0.000004645639,0.00001322153,0.00007549406,0.000007192246,0.0002271973,0.9979722,0.0008046263],"study_design_scores_gemma":[0.0001283522,0.000008774672,0.01574566,0.0006230783,0.00005361398,0.00002359583,0.0004338548,0.0004675066,0.0001740745,0.0005214562,0.9817545,0.00006552616],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004274332,0.00002993576,0.00001272168,0.00006898775,0.00001633398,0.000006336624,0.999275,0.00004472598,0.000503174],"genre_scores_gemma":[0.0003778494,0.0001112808,0.0001297972,0.00006006826,0.0000102967,0.00004500806,0.9975531,0.00005132695,0.001661437],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07662731,"threshold_uncertainty_score":0.2588834,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02806591639339614,"score_gpt":0.2371713160428474,"score_spread":0.2091053996494512,"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."}}