{"id":"W6938922104","doi":"10.6068/dp14ba8fe179b83","title":"Most Recent Data (2005). Statistics Canada. CANSIM: Information and Communications Technology - Information and Communications Technology Sector | Country: Canada | Table: Survey of innovation, logging and manufacturing industries, percentage of plants with new machinery or equipment supplied from different locations | Variable: From Europe, Plants that bought new machinery or equipment, Navigational, measuring, medical and control instruments manufacturing, All plants | Units: %, 2005. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-127.","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; Official statistics; Census; Summary statistics; Information and Communications Technology; Telecommunications equipment; Information technology; Publication; Business 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002347781,0.002473236,0.002913155,0.009654616,0.003964565,0.00518796,0.004985211,0.001598123,0.09767444],"category_scores_gemma":[0.02255042,0.001657691,0.002012038,0.05294252,0.0007064352,0.00249363,0.002294953,0.003108846,0.05732116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06025497,"about_ca_system_score_gemma":0.1581321,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.99516,"about_ca_topic_score_gemma":0.9936248,"domain_scores_codex":[0.99413,0.0003214429,0.0006436195,0.0006538601,0.002981178,0.001269897],"domain_scores_gemma":[0.9522368,0.001765869,0.001262851,0.001095993,0.04171101,0.001927439],"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":[0.00001662232,0.000006330988,0.000807616,0.0002214972,0.00001486096,0.000005455795,0.00001848164,0.0000877512,0.000006660647,0.000288012,0.9972881,0.001238655],"study_design_scores_gemma":[0.0001505394,0.00001226968,0.02649283,0.0008246498,0.0000768833,0.00002344207,0.0005667076,0.0003418022,0.0001595311,0.0005468368,0.970718,0.00008648419],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004713063,0.00005283326,0.00001731344,0.0001126824,0.00002397467,0.00001163434,0.9988657,0.00004171455,0.0008270661],"genre_scores_gemma":[0.0008487829,0.0003145335,0.0003728512,0.0001918882,0.00001948602,0.0001094382,0.9934704,0.00008550905,0.004587143],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9023256,"threshold_uncertainty_score":0.4371824,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04909240181407629,"score_gpt":0.2622216610951266,"score_spread":0.2131292592810503,"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."}}