{"id":"W6939031861","doi":"10.6068/dp14ba8bc39fc58","title":"Trend 1998 - 2011. Statistics Canada. CANSIM: Construction - Residential Construction | Country: Canada | Table: Capital expenditures on construction, by type of asset and North American Industry Classification System (NAICS) sector | Variable: Rail track and roadbeds including signals (x 1,000,000), Management of companies and enterprises | Units: $CAD, 1998-2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-037.","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; Summary statistics; Stock (firearms); Asset (computer security); Index (typography); Publication; Descriptive 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":[0.001466459,0.002255129,0.002248514,0.008162963,0.002765979,0.004347372,0.004456335,0.00133884,0.07438008],"category_scores_gemma":[0.01413941,0.001542263,0.001705516,0.03633134,0.0005585987,0.002322591,0.002039392,0.002675155,0.04714768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04221718,"about_ca_system_score_gemma":0.09351142,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9923145,"about_ca_topic_score_gemma":0.9916015,"domain_scores_codex":[0.9966073,0.0001764618,0.0003434305,0.0004737234,0.001625769,0.0007732832],"domain_scores_gemma":[0.9722723,0.0009471906,0.00101256,0.0008005675,0.02376436,0.001203006],"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":[0.00002262791,0.00000719209,0.001465496,0.0002017004,0.00001934205,0.000007555382,0.00002106771,0.0001307464,0.000008323515,0.0003671802,0.9962655,0.001483395],"study_design_scores_gemma":[0.0001345077,0.00001217426,0.03053455,0.000664276,0.00005705016,0.0000276006,0.0004783366,0.0005428219,0.0001942077,0.0005605429,0.9667187,0.00007515326],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007204075,0.00003907889,0.0000193143,0.00008485415,0.00001729949,0.000009291793,0.9990096,0.00004565105,0.0007028439],"genre_scores_gemma":[0.0007798901,0.000190622,0.0002141827,0.0000798377,0.00001204534,0.00007210857,0.9954184,0.00006605189,0.003166751],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07438008,"threshold_uncertainty_score":0.3063085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03180717853086198,"score_gpt":0.255427078179809,"score_spread":0.223619899648947,"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."}}