{"id":"W6976482477","doi":"10.6068/dp14ba88b6cce68","title":"Trend 1999 - 2003. Statistics Canada. CANSIM: Business, Consumer and Property Services - Arts, Entertainment and Recreation | Country: Canada | Table: Canadian financial summary of performing arts, by discipline and company size | Variable: Opera, Unearned revenue from municipal sector, Large size companies | Units: $CAD x 1,000, 1999-2003. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-010.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"X-ray Spectroscopy and Fluorescence Analysis","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Recreation; Census; Revenue; Entertainment; Amusement; Descriptive statistics; Socioeconomic status; Economic statistics; Tourism; Publication","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002830724,0.0005779516,0.001022598,0.00005363877,0.0003104965,0.0002312641,0.0006371368,0.0001937517,0.001621676],"category_scores_gemma":[0.00006392407,0.0004885253,2.147273e-7,0.0004806932,0.0002279844,0.0002701574,0.000353181,0.0004626185,0.000001813489],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001260648,"about_ca_system_score_gemma":0.0078703,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9999756,"about_ca_topic_score_gemma":0.9998999,"domain_scores_codex":[0.9972287,0.0001776212,0.0006465224,0.0008415137,0.0004852019,0.0006204673],"domain_scores_gemma":[0.9975278,0.0002612283,0.0004691915,0.001057152,0.0001881753,0.0004964605],"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":[0.00009115411,0.00006825837,0.00152201,0.0003418997,0.0003775659,0.00004509562,0.00002008085,0.000006850453,0.00001439029,0.0001781353,0.9972243,0.0001102665],"study_design_scores_gemma":[0.0008884505,0.00003663086,0.0001324569,0.0001667111,0.0006551672,0.000006093598,0.0005974557,0.007019445,1.807039e-7,3.638642e-7,0.9899302,0.0005668245],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005613395,0.005016639,0.000005509822,0.000006572559,0.0002047814,0.0004656702,0.9938152,0.00001066905,0.0004187748],"genre_scores_gemma":[0.0004264685,0.001389521,0.00024879,0.0001411863,0.0001822366,0.00001492603,0.9958009,0.00008429356,0.001711665],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.007744235,"threshold_uncertainty_score":0.9997566,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01267415549097018,"score_gpt":0.2269236240674961,"score_spread":0.2142494685765259,"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."}}