{"id":"W6920507980","doi":"10.6068/dp14ba8c85fff43","title":"Trend 1961 - 2013. Statistics Canada. CANSIM: Construction - Nonresidential Engineering Construction | Country: Canada | Table: Flows and stocks of fixed non-residential capital, by sector of North American Industry Classification System (NAICS) and asset | Variable: Straight-line depreciation, Building (x 1,000,000), Retail trade, 2007 constant prices | Units: $CAD, 1961-2013. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-036.","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; Census; Official statistics; Stock (firearms); Descriptive statistics; Summary statistics; Index (typography); Publication; National accounts","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":[0.001362838,0.002292525,0.002231756,0.008314858,0.002715786,0.00419988,0.004660062,0.001369177,0.07365888],"category_scores_gemma":[0.0142479,0.001492503,0.001786207,0.03813674,0.0005954703,0.002276876,0.002027928,0.002787094,0.04754568],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04137545,"about_ca_system_score_gemma":0.1014511,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9928685,"about_ca_topic_score_gemma":0.9915017,"domain_scores_codex":[0.9969042,0.0001466753,0.0003012546,0.0004399969,0.001464542,0.0007433049],"domain_scores_gemma":[0.9725719,0.0009334387,0.0009164531,0.0007757128,0.02363661,0.001165791],"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":[0.00001931339,0.000006569883,0.001229376,0.000199213,0.00001834661,0.000006668089,0.00001748204,0.0001323657,0.000009242075,0.0003740925,0.9965683,0.001418978],"study_design_scores_gemma":[0.0001370002,0.00001080926,0.02616548,0.0007112877,0.00005856472,0.0000249662,0.0003988488,0.0005288458,0.0002001605,0.0006427686,0.971049,0.00007211675],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005731703,0.00003896742,0.00001862632,0.00007918612,0.00001790015,0.000008499315,0.9990647,0.00004635508,0.0006684295],"genre_scores_gemma":[0.0007165321,0.0001958955,0.0002266869,0.00008854857,0.00001325161,0.00006514322,0.9956934,0.00006543156,0.002935059],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07365888,"threshold_uncertainty_score":0.3002013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01655328644323265,"score_gpt":0.2264574054719109,"score_spread":0.2099041190286782,"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."}}