{"id":"W6888973247","doi":"10.25318/3610045701-eng","title":"Financial flows, segregated funds of life insurance companies, quarterly, 1961 - 2012","year":2019,"lang":"en","type":"dataset","venue":"Statistics Canada Dissemination","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Life insurance; Table (database); Net worth; General insurance; Life table","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":[0.0006324921,0.001206517,0.001075683,0.007042033,0.0007898641,0.002645833,0.001501627,0.0009604801,0.03574452],"category_scores_gemma":[0.008149805,0.0007006604,0.0006790539,0.01841577,0.0002944593,0.001194306,0.0008894963,0.001584183,0.03694608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006279295,"about_ca_system_score_gemma":0.009947988,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6456552,"about_ca_topic_score_gemma":0.6241726,"domain_scores_codex":[0.9986209,0.00006222097,0.0001917715,0.0002443952,0.000607539,0.0002732196],"domain_scores_gemma":[0.9940248,0.0005570907,0.0009166335,0.0003954692,0.003711283,0.000394577],"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":[0.00004658914,0.00001984568,0.004461871,0.000232961,0.00002081613,0.00001231568,0.00002351037,0.0002117983,0.00002793582,0.0004062631,0.9924318,0.002104355],"study_design_scores_gemma":[0.0002056079,0.00002333593,0.09326895,0.0003931758,0.00005180087,0.00007353273,0.0002431135,0.0005264353,0.000399495,0.0004013666,0.9043605,0.0000527218],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003376532,0.00005005689,0.0000104214,0.00003914649,0.00001079677,0.000004449128,0.9989564,0.00003952484,0.0005514498],"genre_scores_gemma":[0.001412681,0.0001489107,0.00006655876,0.00002398891,0.00001251264,0.00003468717,0.9962226,0.00001901935,0.002059134],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3543448,"threshold_uncertainty_score":0.7128632,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009767799248162717,"score_gpt":0.2525590260492735,"score_spread":0.2427912268011108,"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."}}