{"id":"W6976215332","doi":"10.6068/dp14ba8e777b921","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 that have a source of the license | Variable: Plants that acquired licenses, Fabricated metal product manufacturing, Canadian firm, Innovative 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":"European Monetary and Fiscal Policies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economic statistics; Official statistics; Census; Summary statistics; License; Information and Communications Technology; Product (mathematics); Information technology; 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":[],"consensus_categories":[],"category_scores_codex":[0.002497746,0.002508562,0.002721835,0.009784412,0.004160011,0.005377547,0.005166285,0.001635041,0.1035931],"category_scores_gemma":[0.02349685,0.001720735,0.001966505,0.05196658,0.0007246473,0.00264228,0.002285365,0.003179984,0.06295373],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06171696,"about_ca_system_score_gemma":0.1584543,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.994808,"about_ca_topic_score_gemma":0.9929239,"domain_scores_codex":[0.9940004,0.000315162,0.0006296712,0.0006453286,0.003078308,0.001331016],"domain_scores_gemma":[0.9475875,0.001816769,0.001273738,0.001232751,0.04605307,0.002036107],"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":[0.00001626426,0.000006706118,0.0007674292,0.0002024679,0.00001239254,0.000005383648,0.00001830661,0.00008158894,0.000007166011,0.0002764979,0.9973243,0.001281486],"study_design_scores_gemma":[0.0001353713,0.00001168808,0.02472652,0.0007568186,0.00006264584,0.00002122561,0.0005194999,0.0003012454,0.0001596678,0.0005035293,0.9727249,0.00007690278],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004490191,0.000044033,0.00001740079,0.0001083877,0.00002409016,0.00001311735,0.998778,0.00004273221,0.0009273078],"genre_scores_gemma":[0.0007564196,0.0002804069,0.0003663137,0.0001742515,0.00001860647,0.0001194554,0.9934586,0.00009047275,0.004735517],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1035931,"threshold_uncertainty_score":0.44779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05572749177593043,"score_gpt":0.2307783210540307,"score_spread":0.1750508292781003,"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."}}