{"id":"W6901512236","doi":"10.6068/dp14ba84fea0d41","title":"Trend 1999 - 2003. Statistics Canada. CANSIM: Culture and Leisure - Government Spending on Culture | Country: Canada | Table: Federal government expenditures on culture, by culture activity | Variable: Literary arts, Federal government capital expenditures | Units: $CAD x 1,000, 1999-2003. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-047.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Economic statistics; Census; Official statistics; Population; Government spending; Socioeconomic status; Descriptive statistics; Statistics education","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":[0.001988091,0.002364226,0.002523225,0.008934424,0.003123432,0.004615311,0.004755782,0.001350222,0.08055404],"category_scores_gemma":[0.01520252,0.001620582,0.002045149,0.04033351,0.0005927173,0.002397808,0.00211534,0.002940596,0.04440229],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05806901,"about_ca_system_score_gemma":0.1404668,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.995681,"about_ca_topic_score_gemma":0.9943213,"domain_scores_codex":[0.995924,0.0002338664,0.0003821871,0.0004693354,0.00203067,0.0009600352],"domain_scores_gemma":[0.9712822,0.0008647672,0.0008743522,0.0007353942,0.02482732,0.001416054],"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":[0.00002442378,0.000007169055,0.001092648,0.000207233,0.00001930479,0.000007231542,0.0000204124,0.0001119991,0.000008469555,0.0004174171,0.9962979,0.001785831],"study_design_scores_gemma":[0.0001428528,0.00001251877,0.02852124,0.0007470386,0.00006898167,0.00002621202,0.0004836364,0.0005496607,0.0001868566,0.0006717694,0.9685099,0.0000793408],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006843959,0.00005982442,0.00002560449,0.0001476445,0.0000306143,0.00001462085,0.998495,0.00005750296,0.001100736],"genre_scores_gemma":[0.001143858,0.0003422151,0.0004195899,0.0001753378,0.00002070844,0.0001226219,0.9918187,0.0001166768,0.00584032],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08055404,"threshold_uncertainty_score":0.4213221,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01727361137898104,"score_gpt":0.243232726034723,"score_spread":0.225959114655742,"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."}}