{"id":"W6976395278","doi":"10.6068/dp14ba902f8a95","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 the plant's total revenue that came from the sale of products to clients by geographical markets | Variable: Sale of products to clients in Asia, Information and communication technology (ICT) manufacturing industries, 25% to 49% of the plant's total revenue, 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":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economic statistics; Official statistics; Census; Revenue; Summary statistics; Business statistics; Descriptive statistics; Information and Communications Technology; Information technology","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":[0.0022781,0.002388048,0.002783046,0.0100853,0.003880176,0.005280525,0.005131584,0.001626554,0.08471218],"category_scores_gemma":[0.0217701,0.001615701,0.002124409,0.05241015,0.0006963129,0.002501002,0.002293459,0.003206923,0.05073055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05857307,"about_ca_system_score_gemma":0.1568858,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9948945,"about_ca_topic_score_gemma":0.9933673,"domain_scores_codex":[0.9944437,0.0003127439,0.0006276508,0.0006129865,0.002729689,0.00127325],"domain_scores_gemma":[0.95347,0.001732707,0.001261822,0.001071659,0.04064374,0.001820135],"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":[0.00001807554,0.000007454148,0.000944165,0.0002423583,0.0000164732,0.000006044013,0.00001878677,0.00009505081,0.000006423126,0.000302703,0.9971203,0.001222214],"study_design_scores_gemma":[0.0001399798,0.00001207077,0.02770953,0.0008839436,0.00007654895,0.00002399425,0.0006169927,0.0003688336,0.0001614893,0.0004984435,0.9694244,0.00008372738],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005091555,0.00005552194,0.00001392453,0.0001151115,0.00002345118,0.00001042346,0.9989797,0.00003686178,0.0007140181],"genre_scores_gemma":[0.0008238476,0.0003008782,0.0002792995,0.000169013,0.00001802515,0.00009720109,0.9943445,0.00006709839,0.003900226],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08471218,"threshold_uncertainty_score":0.4249794,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0301819865385499,"score_gpt":0.2394994635274821,"score_spread":0.2093174769889322,"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."}}