{"id":"W214991793","doi":"","title":"Un modelo de balance actuarial para sistemas de pensiones DB PAYG con dos contingencias.","year":2013,"lang":"es","type":"article","venue":"Dialnet (Universidad de la Rioja)","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Social security; Welfare economics; Solvency; Balance (ability); Economics; Actuarial science; Pension plan; Pension; Political science; Psychology; Finance; Market liquidity","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002176228,0.0005531143,0.0007632949,0.0003569156,0.001226895,0.0007720903,0.001130155,0.0006948977,0.0008015947],"category_scores_gemma":[0.0002805338,0.0006275722,0.0004913885,0.000991813,0.001139266,0.0009165601,0.0003038151,0.0005894636,0.000426775],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000553612,"about_ca_system_score_gemma":0.0004977456,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0286631,"about_ca_topic_score_gemma":0.001673075,"domain_scores_codex":[0.9944004,0.001714385,0.0004979981,0.0008473987,0.0009544879,0.00158531],"domain_scores_gemma":[0.9971634,0.0007057771,0.0005542861,0.0007029028,0.0003193049,0.0005543185],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004507799,0.001107159,0.6312426,0.0005191512,0.001293605,0.0007587909,0.06665697,0.00137285,0.003406077,0.2366015,0.02438446,0.0322061],"study_design_scores_gemma":[0.003082532,0.0001560734,0.9026494,0.0002507677,0.0005959389,0.00001149736,0.013579,0.01123958,0.0002559705,0.01365391,0.05322675,0.00129859],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9356971,0.0004825031,0.001848986,0.002568411,0.0008306177,0.001279966,0.00005915543,0.0002540766,0.05697921],"genre_scores_gemma":[0.9930203,0.00222931,0.001813134,0.0008047401,0.0007216857,0.0000584676,0.00002475453,0.00006295143,0.001264667],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2714068,"threshold_uncertainty_score":0.9996176,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01279291138501308,"score_gpt":0.2660234021683002,"score_spread":0.2532304907832871,"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."}}