{"id":"W6976525468","doi":"10.6068/dp14ba896ec7011","title":"Trend 1998 - 2005. Statistics Canada. CANSIM: Culture and Leisure - Trade in Culture Goods and Services | Country: Canada | Table: Employment, salaries and benefits for Canadian and foreign controlled film, video and audio-visual distribution and videocassettes wholesaling companies, by employment characteristics 1997/1998 to 2004/2005 | Variable: Total salaries and benefits, Canadian and foreign controlled companies | Units: $CAD x 1,000, 1998-2005. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-055.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"Climate Change Communication and Perception","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Official statistics; Goods and services; Summary statistics; Economic statistics; Portrait; Distribution (mathematics); National accounts","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":[0.001523375,0.002541903,0.002822986,0.008312598,0.003009787,0.004806015,0.004957708,0.00153449,0.07549991],"category_scores_gemma":[0.01344135,0.001615112,0.002112469,0.0387316,0.0006711595,0.00245115,0.002264573,0.003271053,0.04999479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03788972,"about_ca_system_score_gemma":0.094354,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9921712,"about_ca_topic_score_gemma":0.9907175,"domain_scores_codex":[0.9965535,0.0001893512,0.0003730826,0.0004948054,0.001524825,0.0008645079],"domain_scores_gemma":[0.9761013,0.0009127991,0.0009796735,0.0007141748,0.0200396,0.00125248],"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":[0.00002303902,0.000007077318,0.001223014,0.0002132268,0.00002125395,0.000006427854,0.00001588859,0.00009731448,0.000007568975,0.0002571405,0.9969305,0.001197511],"study_design_scores_gemma":[0.000195568,0.00001505429,0.03044885,0.0008893876,0.00007766695,0.00002765207,0.0005207167,0.0005631807,0.0001771463,0.0006095385,0.9663921,0.000083201],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005506503,0.00004582254,0.00001439095,0.00009472566,0.00002397782,0.000008356405,0.9991657,0.00004011055,0.0005519058],"genre_scores_gemma":[0.000653045,0.0002041612,0.0001679973,0.0001066809,0.00001653302,0.00006977635,0.996086,0.00005358496,0.002642145],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07549991,"threshold_uncertainty_score":0.2749104,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05057554061777918,"score_gpt":0.2900566882916392,"score_spread":0.23948114767386,"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."}}