{"id":"W6938805705","doi":"10.6068/dp14ba8e3700095","title":"Trend 1961 - 2013. Statistics Canada. CANSIM: Labor - Industries | Country: Canada | Table: Flows and stocks of fixed non-residential capital, by sector of North American Industry Classification System (NAICS) and asset | Variable: Hyperbolic (delayed) depreciation, Machinery and equipment (x 1,000,000), Other services (except public administration), Current prices | Units: $CAD, 1961-2013. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-139.","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; Asset (computer security); Wages and salaries; Publication; Statistical analysis; Population 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":[0.001786214,0.002318301,0.002708047,0.008655103,0.003090606,0.004406903,0.005051919,0.001466331,0.08858697],"category_scores_gemma":[0.01675311,0.001660341,0.002017059,0.04238293,0.0006077868,0.002328268,0.002263415,0.002855605,0.05410824],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04823294,"about_ca_system_score_gemma":0.1212386,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9945745,"about_ca_topic_score_gemma":0.992817,"domain_scores_codex":[0.9963133,0.0002118343,0.0003948948,0.000506517,0.001669702,0.0009038344],"domain_scores_gemma":[0.967382,0.001151901,0.001007049,0.0009308505,0.02806487,0.001463417],"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":[0.00002324966,0.000006625611,0.00112401,0.0002295973,0.00002066965,0.000006508201,0.00002127219,0.0001160721,0.000009501689,0.0003639922,0.9965881,0.001490396],"study_design_scores_gemma":[0.0001695253,0.00001282346,0.02720119,0.0008393649,0.00007256524,0.00002685559,0.0004853403,0.0004843887,0.0002091592,0.0007187118,0.9696913,0.00008874258],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005173198,0.00004212568,0.00002028376,0.00009057971,0.00002233245,0.00001064691,0.9990411,0.00005168498,0.0006694476],"genre_scores_gemma":[0.0007926745,0.0002368075,0.0003210983,0.0001261646,0.00001727722,0.00009441911,0.9944326,0.00009120578,0.003887638],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08858697,"threshold_uncertainty_score":0.3499562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02281185825459738,"score_gpt":0.2505718919169359,"score_spread":0.2277600336623385,"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."}}