{"id":"W2565261140","doi":"10.1057/s10713-020-00058-9","title":"Pensions, annuities, and long-term care insurance: on the impact of risk screening","year":2020,"lang":"en","type":"article","venue":"The Geneva Risk and Insurance Review","topic":"Financial Literacy, Pension, Retirement Analysis","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; HEC Montréal","funders":"","keywords":"Actuarial science; Group insurance; Long-term care insurance; Purchasing; Context (archaeology); Business; Product (mathematics); Pension; Term (time); Economics; Long-term care; Insurance policy; Income protection insurance; General insurance; Marketing; Finance; Medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.01986431,0.0008945731,0.001689538,0.008110319,0.0003773336,0.004392069,0.001139058,0.002677366,0.003866848],"category_scores_gemma":[0.04667275,0.0004097899,0.0009467459,0.008770416,0.001813335,0.003101004,0.00182958,0.002176199,0.0007170556],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004854081,"about_ca_system_score_gemma":0.01218208,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03467451,"about_ca_topic_score_gemma":0.07032196,"domain_scores_codex":[0.9894879,0.004980418,0.001367469,0.00039666,0.00319413,0.0005734779],"domain_scores_gemma":[0.9460366,0.03275674,0.005912305,0.0009090095,0.01247838,0.001906905],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0006529313,0.00006987186,0.004543132,0.01283508,0.0002985619,0.00009873792,0.0003169833,0.0007660396,0.0001660396,0.01294784,0.1738563,0.7934483],"study_design_scores_gemma":[0.0001632843,0.0003219088,0.04219992,0.05585882,0.00118625,0.0003314998,0.0005667473,0.0003788227,0.0002867171,0.003792095,0.8948308,0.0000831392],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.000507377,0.9865294,0.00005477566,0.009590148,0.0008769779,0.000007579069,0.0001721373,0.000007136041,0.002254608],"genre_scores_gemma":[0.01004085,0.9834889,0.0001903784,0.003549652,0.001653474,0.00001857306,0.0002544748,0.00001395895,0.0007897777],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03467451,"threshold_uncertainty_score":0.1050537,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02527155032978168,"score_gpt":0.2647591440776353,"score_spread":0.2394875937478537,"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."}}