{"id":"W6920633528","doi":"10.6068/dp14ba8c0329b77","title":"Most Recent Data (2003). Statistics Canada. CANSIM: Seniors - Work and Retirement | Country: Canada | Table: Survey of innovation, selected service industries, type of organizations with which innovative business units cooperated and collaborated in order to develop products or processes | Variable: Computer systems design and related services, Suppliers of equipment, materials, components or software | Units: %, 2003. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-186.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"Lymphatic System and Diseases","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Economic statistics; Work (physics); Official statistics; Service (business); Socioeconomic status; Population; Publication; Descriptive 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":[0.002424363,0.002409652,0.002896243,0.00845556,0.003924199,0.005112679,0.005419942,0.001628344,0.08789439],"category_scores_gemma":[0.02140573,0.001777876,0.002152913,0.04613714,0.0006794611,0.002306656,0.002491772,0.003114086,0.05611055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05532742,"about_ca_system_score_gemma":0.1400477,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9951331,"about_ca_topic_score_gemma":0.9937578,"domain_scores_codex":[0.9950706,0.0002888876,0.0006392763,0.0005843196,0.002248201,0.001168693],"domain_scores_gemma":[0.9537134,0.001775384,0.001277161,0.00115587,0.03999504,0.002083112],"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":[0.00002215877,0.000007313796,0.001010171,0.0002617005,0.00001604283,0.000005190944,0.00002297232,0.00006765895,0.000006860292,0.0002054074,0.9972633,0.001111315],"study_design_scores_gemma":[0.0002479489,0.00001624847,0.04159136,0.001170532,0.0001028817,0.00002515053,0.0007862998,0.0003549892,0.000184785,0.0005227531,0.9548931,0.0001039284],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004434193,0.00003803865,0.00001249143,0.0000857358,0.00001754067,0.00001211441,0.9991657,0.00003357488,0.0005904335],"genre_scores_gemma":[0.0007006245,0.0002383309,0.0002574376,0.0001552953,0.00001557219,0.0001295343,0.9951243,0.00007007144,0.003308803],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08789439,"threshold_uncertainty_score":0.4014304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04400170505685843,"score_gpt":0.2532818035600716,"score_spread":0.2092800985032132,"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."}}