{"id":"W2128761671","doi":"10.5267/j.msl.2012.12.010","title":"Measuring liquidity risk in Social Security using VaR technique","year":2013,"lang":"en","type":"article","venue":"Management Science Letters","topic":"Insurance and Financial Risk Management","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Market liquidity; Computer science; Social security; Business; Econometrics; Risk analysis (engineering); Finance; Economics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.001257937,0.0004023945,0.000472348,0.001452524,0.0002843604,0.001079089,0.0004166833,0.0006919552,0.0009641691],"category_scores_gemma":[0.003875243,0.0001856726,0.000487637,0.001047455,0.0003643701,0.0011298,0.0006846305,0.0007857554,0.0001566083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003563885,"about_ca_system_score_gemma":0.0003093368,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003235772,"about_ca_topic_score_gemma":0.001580212,"domain_scores_codex":[0.9994308,0.0002398019,0.00003113027,0.00008279536,0.0001354501,0.00007995238],"domain_scores_gemma":[0.9984811,0.0009350391,0.0002906478,0.00008847789,0.0001439898,0.00006073618],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007453561,0.0002459957,0.2164125,0.0002546231,0.0006650888,0.001558031,0.0005574964,0.5654455,0.04133302,0.06266841,0.001842962,0.108271],"study_design_scores_gemma":[0.00001894387,0.000160517,0.0322182,0.00002549833,0.00004747334,0.000177496,0.0001034962,0.9484358,0.003692374,0.0146284,0.0004431462,0.0000485825],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8435546,0.0006195031,0.1518029,0.0003432516,0.0000358658,0.00002628677,0.0002330488,0.0002287096,0.003155908],"genre_scores_gemma":[0.9938217,0.0001128754,0.005592998,0.0000133563,0.00001627714,0.000007717332,0.00009254499,0.000006747579,0.0003357764],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003235772,"threshold_uncertainty_score":0.006652713,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03532416401906329,"score_gpt":0.2206123599158678,"score_spread":0.1852881958968045,"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."}}