{"id":"W6976663082","doi":"10.6068/dp14ba861871e15","title":"Trend 2001 - 2011. Statistics Canada. CANSIM: Business, Consumer and Property Services - Accommodation and Food | Country: Canada | Table: Food services and drinking places, summary statistics, by North American Industry Classification System (NAICS) | Variable: Food services and drinking places, Operating expenses (x 1,000,000) | Units: , 2001-2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-009.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Official statistics; Tourism; Census; Economic statistics; Summary statistics; Accommodation; Hospitality; Hospitality industry; Service (business)","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":[0.002347613,0.002520493,0.002786499,0.00844784,0.003196124,0.004831099,0.005384979,0.001559446,0.09468332],"category_scores_gemma":[0.02042141,0.001909532,0.002148601,0.0435064,0.000649359,0.002736161,0.002256363,0.003383838,0.05823753],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05080095,"about_ca_system_score_gemma":0.1400861,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9938379,"about_ca_topic_score_gemma":0.9918749,"domain_scores_codex":[0.9955408,0.0003072089,0.0004976963,0.0005716871,0.002066759,0.001015784],"domain_scores_gemma":[0.9612241,0.001427416,0.001125295,0.001100327,0.03334699,0.001775906],"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":[0.00002107009,0.000005350693,0.0008351479,0.0002285415,0.00001801396,0.000005823087,0.0000174298,0.00009685893,0.000007596345,0.000285796,0.997094,0.001384219],"study_design_scores_gemma":[0.0001580589,0.00001306128,0.02402748,0.000965073,0.00008095193,0.00002888702,0.0004651794,0.0004910913,0.000164364,0.0006497017,0.9728706,0.00008548117],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004858426,0.00005123184,0.00002457031,0.0001364439,0.00002898801,0.00001381854,0.9988593,0.0000567247,0.0007803654],"genre_scores_gemma":[0.0007246172,0.0003140291,0.0003881038,0.0001782833,0.00002109397,0.00012342,0.9939644,0.0001220587,0.004164003],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09468332,"threshold_uncertainty_score":0.3685884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02928053732794872,"score_gpt":0.2344562068166269,"score_spread":0.2051756694886782,"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."}}