{"id":"W6901643577","doi":"10.6068/dp14ba81c71b038","title":"Trend 2007 - 2011. Statistics Canada. CANSIM: Business, Consumer and Property Services - Accommodation and Food | Country: Canada | Table: Traveller accommodation, operating expenses, by North American Industry Classification System (NAICS) | Variable: Repair and maintenance, Accommodation services | Units: %, 2007-2011. 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; Accommodation; Census; Tourism; Economic statistics; Summary statistics; Hospitality industry; Hospitality","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":["metaepi_narrow"],"category_scores_codex":[0.001183353,0.001474719,0.001688137,0.0002503143,0.0006186673,0.000975051,0.001935398,0.0008632708,0.001206121],"category_scores_gemma":[0.0000783159,0.00128064,3.209785e-7,0.0006489615,0.0005685678,0.001798554,0.001090492,0.001433632,0.0000716202],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006124747,"about_ca_system_score_gemma":0.009430635,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9994943,"about_ca_topic_score_gemma":0.9989963,"domain_scores_codex":[0.9919769,0.001004938,0.001824505,0.002452546,0.001584387,0.001156753],"domain_scores_gemma":[0.9917216,0.0006147543,0.002606716,0.003496279,0.0006700106,0.0008906477],"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":[0.0001542648,0.0001046724,0.001597466,0.002887227,0.0005593474,0.00005035346,0.00001082374,0.00003124398,0.000008843626,0.0001302968,0.9941495,0.0003159812],"study_design_scores_gemma":[0.001409447,0.00008525608,0.0005888547,0.0002033587,0.0008078038,0.0002734562,0.002603217,0.03260412,3.844853e-8,6.478831e-8,0.9598916,0.001532795],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002917839,0.002858114,0.00001689129,0.00001278454,0.0005050163,0.001904723,0.9931374,0.0002952735,0.001240624],"genre_scores_gemma":[0.0003799006,0.001587028,0.0006251406,0.0004374979,0.00031136,0.0001132745,0.9948833,0.0005808844,0.001081603],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03425789,"threshold_uncertainty_score":0.9998002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02440604239718298,"score_gpt":0.2338448467127427,"score_spread":0.2094388043155598,"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."}}