{"id":"W6958028745","doi":"10.6068/dp14ba8dcfc5721","title":"Most Recent Data (2003). Statistics Canada. CANSIM: Economic Accounts - Environmental and Resource Accounts | Country: Canada | Table: Survey of innovation, selected service industries, percentage of total revenues from the sale of products to the mining and/or forestry and/or forest products industries | Variable: Mining industry, Cable and other program distribution, 50% to 74% of revenues, Non-innovative business units | Units: %, 2003. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-058.","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; Revenue; National accounts; Census; Summary statistics; Service (business); Descriptive statistics; Economic data; Natural resource","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":[0.001990746,0.002290805,0.002599794,0.0097389,0.003415625,0.005160463,0.004715217,0.001531705,0.09420656],"category_scores_gemma":[0.01862163,0.001608801,0.001789571,0.05571513,0.0006822896,0.002380667,0.001979843,0.003052494,0.06074534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06093187,"about_ca_system_score_gemma":0.1349287,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9943435,"about_ca_topic_score_gemma":0.9922938,"domain_scores_codex":[0.9952867,0.0002429927,0.000525463,0.0005402332,0.002373635,0.001030905],"domain_scores_gemma":[0.9580112,0.001537667,0.001134817,0.001051657,0.03675352,0.001511193],"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":[0.00001586566,0.000006011607,0.000704084,0.0001824005,0.00001246022,0.000005671183,0.00001623749,0.00008563024,0.000006852166,0.000267301,0.9976394,0.001058082],"study_design_scores_gemma":[0.0001231255,0.000008586421,0.023904,0.0006297541,0.00005475303,0.00002023935,0.0004788505,0.0003626242,0.0001550567,0.0004879819,0.9736993,0.00007577385],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004229844,0.00003669667,0.00001182811,0.00008909569,0.00001850898,0.00001005647,0.9989482,0.00003681294,0.0008065635],"genre_scores_gemma":[0.0007091737,0.0002322188,0.0002578945,0.0001284899,0.00001513838,0.00009653472,0.9945614,0.00006937305,0.003929773],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09420656,"threshold_uncertainty_score":0.4420937,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04091836657232849,"score_gpt":0.2532377768177613,"score_spread":0.2123194102454328,"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."}}