{"id":"W6976558917","doi":"10.6068/dp14baa2f9b8e50","title":"Trend 1999 - 2005. Statistics Canada. CANSIM: Business, Consumer and Property Services - Personal Services | Country: Canada | Province: New Brunswick | Table: Personal services, summary statistics, by North American Industry Classification System (NAICS) | Variable: Dry cleaning and laundry services, Number of establishments | Units: # Units, 1999-2005. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-012.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Economic statistics; Official statistics; Socioeconomic status; Descriptive statistics; Personal income; Laundry; Summary statistics; 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":[0.001970068,0.002555324,0.002746892,0.01014744,0.003534218,0.005173954,0.005608052,0.001510767,0.08941744],"category_scores_gemma":[0.01829591,0.001846968,0.002046702,0.04863454,0.0006821058,0.002745404,0.00224235,0.00308719,0.05245963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05674344,"about_ca_system_score_gemma":0.1465089,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.995333,"about_ca_topic_score_gemma":0.9940618,"domain_scores_codex":[0.9953076,0.0002677369,0.0005031117,0.0006432984,0.002138952,0.00113938],"domain_scores_gemma":[0.9652086,0.001281588,0.001159314,0.001005046,0.02962572,0.001719606],"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":[0.00001861319,0.000005427488,0.0008708309,0.0001939228,0.00001833051,0.000006456116,0.00001992044,0.0001019563,0.000008024673,0.0004122741,0.9970944,0.001249885],"study_design_scores_gemma":[0.0001269473,0.00001065784,0.02069904,0.0007232665,0.00006721667,0.00002604555,0.0005201401,0.0004935482,0.000179535,0.0006382104,0.976437,0.00007841633],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005314502,0.00004566704,0.00002311928,0.0001200131,0.00002591942,0.00001192916,0.9987794,0.00004846201,0.0008923603],"genre_scores_gemma":[0.0008329682,0.0002532811,0.000333285,0.000139779,0.0000159052,0.00009110028,0.993865,0.0000935763,0.004375178],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08941744,"threshold_uncertainty_score":0.4117044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0181752099457641,"score_gpt":0.2314930369144569,"score_spread":0.2133178269686928,"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."}}