{"id":"W6957727484","doi":"10.6068/dp14baa3deab457","title":"Trend 1981 - 2012. Statistics Canada. CANSIM: Business, Consumer and Property Services - General | Country: Canada | Province: Quebec | Table: Detailed household final consumption expenditure | Variable: Accommodation services (x 1,000,000), 2007 constant prices | Units: $CAD, 1981-2012. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-008.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economic statistics; Official statistics; Consumption (sociology); Census; National accounts; Accommodation; Summary statistics; Descriptive statistics","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":[0.001819463,0.00244542,0.002724493,0.00879909,0.003472725,0.00503875,0.00498961,0.001593484,0.1171206],"category_scores_gemma":[0.01715886,0.001633026,0.002040367,0.04136927,0.0006496908,0.002739228,0.002147237,0.002895553,0.07100721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05506575,"about_ca_system_score_gemma":0.1255632,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.995274,"about_ca_topic_score_gemma":0.9941795,"domain_scores_codex":[0.9963894,0.0002055857,0.0003498241,0.0005065119,0.001657378,0.0008913761],"domain_scores_gemma":[0.9666275,0.001077098,0.0009492948,0.0009996104,0.02875478,0.001591819],"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":[0.0000186299,0.000005241196,0.0008153305,0.0001919493,0.00001533442,0.000006001032,0.00001738165,0.00008527353,0.000008827081,0.0003081778,0.9971485,0.001379464],"study_design_scores_gemma":[0.0001297092,0.00001082027,0.02191126,0.0006801384,0.0000545255,0.00002341341,0.0003855849,0.0004114478,0.0001573435,0.000486704,0.9756732,0.00007582262],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005087994,0.00004718266,0.00002095538,0.0001052686,0.00002595543,0.00001291047,0.9986934,0.0000588605,0.0009846907],"genre_scores_gemma":[0.0008327853,0.0002420058,0.0002994387,0.0001386335,0.00001996548,0.0001083637,0.9931939,0.0001161108,0.005048842],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1171206,"threshold_uncertainty_score":0.3995318,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02992468382792019,"score_gpt":0.2394251215192003,"score_spread":0.2095004376912801,"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."}}