{"id":"W6901520186","doi":"10.6068/dp14ba8ffa78a50","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 the rest of Canada, Computer and electronic product manufacturing, 0% 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; Revenue; Census; Summary statistics; Product (mathematics); Information and Communications Technology; Descriptive statistics; 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":[0.002196533,0.002432332,0.002788938,0.009973165,0.003818881,0.005169428,0.005017516,0.001610714,0.08029491],"category_scores_gemma":[0.02182451,0.001572173,0.00207665,0.05145955,0.0007114144,0.002428935,0.002259213,0.00324312,0.05055619],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05610237,"about_ca_system_score_gemma":0.1518692,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9948581,"about_ca_topic_score_gemma":0.9934425,"domain_scores_codex":[0.994644,0.0003043706,0.0006299386,0.000614144,0.002617175,0.001190227],"domain_scores_gemma":[0.9551067,0.001708529,0.0012645,0.001109479,0.03905414,0.001756576],"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":[0.00001803577,0.000007069634,0.0009479031,0.0002424323,0.00001701037,0.000006058835,0.00001822654,0.00009658717,0.000006982241,0.0002815366,0.997188,0.001170083],"study_design_scores_gemma":[0.0001558287,0.00001239008,0.02793717,0.0008594165,0.00008130136,0.00002420988,0.000592274,0.0003914136,0.0001630043,0.000527818,0.9691706,0.0000845769],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004933494,0.00005251041,0.00001414342,0.0001089089,0.00002185678,0.00001019848,0.9990638,0.00003657775,0.0006426821],"genre_scores_gemma":[0.0007706899,0.0002749577,0.0002697594,0.0001598296,0.0000169308,0.00009178278,0.995047,0.00006176807,0.003307364],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08029491,"threshold_uncertainty_score":0.4070531,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02416956774571612,"score_gpt":0.2331356130392782,"score_spread":0.2089660452935621,"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."}}