{"id":"W6920223131","doi":"10.6068/dp14ba8e1693b85","title":"Trend 2007 - 2011. Statistics Canada. CANSIM: Business, Consumer and Property Services - Rental and Leasing and Real Estate | Country: Canada | Table: Real estate rental and leasing and property management, summary statistics, by North American Industry Classification System (NAICS) | Variable: Lessors of residential buildings and dwellings (except social housing projects), Operating revenue (x 1,000,000) | Units: , 2007-2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-014.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Real estate; Renting; Census; Property management; Revenue; Real property; Official statistics; Summary 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":[0.001665922,0.002472589,0.002809986,0.008818308,0.002789015,0.004954249,0.005011689,0.001452909,0.0767349],"category_scores_gemma":[0.01636496,0.001714906,0.001913837,0.04446635,0.0006530735,0.002636488,0.002199658,0.003206009,0.06070909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04219166,"about_ca_system_score_gemma":0.1079671,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9916599,"about_ca_topic_score_gemma":0.990279,"domain_scores_codex":[0.9959065,0.0002330808,0.000437094,0.0005946196,0.001864834,0.0009637689],"domain_scores_gemma":[0.9670823,0.001214019,0.001158638,0.0009616247,0.02814953,0.001433932],"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":[0.00001883476,0.000006160888,0.001129299,0.0001754489,0.00001669227,0.000005991587,0.00001528777,0.00009630762,0.000007649725,0.0002593708,0.9971184,0.001150541],"study_design_scores_gemma":[0.0001406363,0.00001213353,0.02817819,0.0007320352,0.00006091356,0.00002724129,0.0004896299,0.0005638566,0.0001905093,0.0005517487,0.9689762,0.00007688645],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006028102,0.00003980226,0.00001706423,0.00008548667,0.00002141409,0.000008504444,0.9991186,0.00004472785,0.0006041535],"genre_scores_gemma":[0.0005531307,0.0001600077,0.0001700342,0.00008103412,0.00001324862,0.00006455941,0.9963683,0.00006006872,0.002529583],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0767349,"threshold_uncertainty_score":0.3061234,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02408900403304187,"score_gpt":0.2426411385856531,"score_spread":0.2185521345526112,"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."}}