{"id":"W3047119936","doi":"10.2139/ssrn.3661876","title":"The Canadian Pension Fund Model: A Quantitative Portrait","year":2020,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Canadian Policy and Governance","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Portrait; Pension; Pension fund; Actuarial science; Business; Economics; Finance; History; Art history","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001517402,0.0005895756,0.0005807431,0.002561707,0.002449483,0.006679544,0.002374734,0.001565699,0.01664381],"category_scores_gemma":[0.005415138,0.0003127401,0.0005288767,0.004209593,0.002873913,0.002680652,0.001038787,0.001324718,0.000559327],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03829416,"about_ca_system_score_gemma":0.03470929,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9324263,"about_ca_topic_score_gemma":0.9227945,"domain_scores_codex":[0.999089,0.0002596872,0.00001928633,0.0000839408,0.0003744302,0.0001736505],"domain_scores_gemma":[0.9986583,0.0005000641,0.00009236976,0.0001020956,0.0004377042,0.0002094526],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00001110742,0.00001031174,0.0008375471,0.00002957801,0.00001104455,0.00002207997,0.0002856517,0.03297061,0.00004647593,0.9553002,0.007050013,0.00342536],"study_design_scores_gemma":[0.00005652955,0.00002525382,0.005643876,0.0001905579,0.00006546758,0.00007269885,0.002220406,0.2246811,0.0001109773,0.6837938,0.08304619,0.00009311565],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1515295,0.005086319,0.06244314,0.03046265,0.0001894605,0.0002432732,0.008624404,0.000504899,0.7409164],"genre_scores_gemma":[0.9373994,0.003069065,0.01049781,0.0005125483,0.00007602679,0.0001392685,0.0007984681,0.00008441715,0.04742302],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06757367,"threshold_uncertainty_score":0.2778448,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04701377484130686,"score_gpt":0.3125600123759752,"score_spread":0.2655462375346683,"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."}}