{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000889243,0.00007837946,0.0001410229,0.00001379018,0.0003791369,0.00007938721,0.0001744928,0.00004661263,0.0002009682],"category_scores_gemma":[0.0004183932,0.0000584407,0.00002269454,0.00007849166,0.0002522158,0.00005836804,0.00002575615,0.0001112162,0.000001997538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001205741,"about_ca_system_score_gemma":0.0001050634,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9690714,"about_ca_topic_score_gemma":0.9662842,"domain_scores_codex":[0.9987292,0.0003594156,0.0001562318,0.0001996011,0.0003254728,0.0002300516],"domain_scores_gemma":[0.9993691,0.000311841,0.00005166225,0.000177334,0.00002041952,0.00006961473],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002284048,0.0001344274,0.8117222,0.000009483749,0.00003135171,0.00002751849,0.06398416,0.00003775052,0.00004110474,0.01383619,0.06502562,0.04492183],"study_design_scores_gemma":[0.0006400378,0.0000170298,0.8450738,0.00004374343,0.00001831618,2.286678e-7,0.006063493,0.00009053887,0.00005967642,0.02837428,0.1194798,0.0001390795],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.932581,0.0009630903,0.000003216407,0.03182873,0.0002368504,0.0002213535,0.0000188842,0.00002027814,0.03412657],"genre_scores_gemma":[0.9969349,0.001497245,0.00005420588,0.0006517282,0.0002036822,0.000003695832,0.000003550769,0.000003608729,0.0006474108],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06435385,"threshold_uncertainty_score":0.2916053,"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."}}