{"id":"W2103605813","doi":"","title":"RISK POOLING AND THE MARKET CRASH: LESSONS FROM CANADA'S PENSION PLAN","year":2009,"lang":"en","type":"article","venue":"Issues in Brief","topic":"Retirement, Disability, and Employment","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Actuary; Pension; Sass; Plan (archaeology); Crash; Pooling; Management; Actuarial science; Economics; Finance; Computer science; History","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":[0.002915571,0.0004989074,0.00059189,0.001686034,0.01093011,0.00861657,0.002565418,0.003872758,0.007012865],"category_scores_gemma":[0.009866393,0.0002877997,0.0007800485,0.002545387,0.00374316,0.004098529,0.002709719,0.007665664,0.0005186395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.09889612,"about_ca_system_score_gemma":0.1428734,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9923849,"about_ca_topic_score_gemma":0.9935511,"domain_scores_codex":[0.9971776,0.0002695351,0.00005515456,0.0001201448,0.001128287,0.001249226],"domain_scores_gemma":[0.9948032,0.0007922387,0.0001918557,0.0001662273,0.003000543,0.001045817],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001391777,0.0001239983,0.03635731,0.000230051,0.00008027731,0.00160749,0.01210642,0.004022079,0.0001712864,0.3921532,0.409344,0.1436647],"study_design_scores_gemma":[0.0000792209,0.000102581,0.08269163,0.001538101,0.0001445206,0.0006348056,0.04843917,0.005409039,0.0003924418,0.08604802,0.7742659,0.0002544911],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.09031624,0.05168341,0.001958976,0.5599214,0.001874452,0.0001352712,0.002505086,0.0001293485,0.2914757],"genre_scores_gemma":[0.819498,0.05982615,0.002109487,0.04580322,0.001066646,0.00006595623,0.001391516,0.0001445858,0.07009444],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.09889612,"threshold_uncertainty_score":0.7175449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08398862528349602,"score_gpt":0.384402217644832,"score_spread":0.300413592361336,"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."}}