{"id":"W6957681854","doi":"10.6068/dp14ba8ecfb9212","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: Geometric (infinite) depreciation, Agricultural machinery (x 1,000,000), Total all industries, 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; Stock (firearms); Official statistics; Descriptive statistics; Publication; Summary statistics; Index (typography); 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":[0.001227513,0.002285473,0.002228626,0.008138265,0.0026595,0.004080846,0.004542348,0.001380739,0.07392251],"category_scores_gemma":[0.01376169,0.001438939,0.001768705,0.03644672,0.000587946,0.002110122,0.001983584,0.002650411,0.04589111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03998436,"about_ca_system_score_gemma":0.09318241,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9929504,"about_ca_topic_score_gemma":0.9921004,"domain_scores_codex":[0.9971778,0.0001329913,0.0002861198,0.0004192153,0.001296309,0.0006875527],"domain_scores_gemma":[0.9756531,0.0008738572,0.000880543,0.0007170038,0.02077923,0.001096177],"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":[0.0000212607,0.000006700519,0.001350707,0.0002163593,0.00001993991,0.000007162071,0.0000186374,0.000137149,0.000009779574,0.0003866146,0.996391,0.001434661],"study_design_scores_gemma":[0.0001509925,0.00001105735,0.02725149,0.0007482483,0.00006339654,0.0000277433,0.0004178173,0.0005660926,0.0002020545,0.0006539571,0.9698345,0.00007269946],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005921568,0.00004166562,0.00001725603,0.00007360983,0.00001630948,0.000007571104,0.9991282,0.00004264739,0.0006135721],"genre_scores_gemma":[0.0007750104,0.0001993338,0.000208355,0.00008441707,0.00001229876,0.00006013595,0.9958913,0.00005746344,0.002711597],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07392251,"threshold_uncertainty_score":0.2901082,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01445133724605161,"score_gpt":0.2153267366828873,"score_spread":0.2008753994368357,"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."}}