{"id":"W1534442344","doi":"10.1002/hec.3506","title":"Individual survival curves comparing subjective and observed mortality risks","year":2017,"lang":"en","type":"article","venue":"Health Economics","topic":"Global Health Care Issues","field":"Health Professions","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal; Université Laval","funders":"National Institute on Aging","keywords":"Life expectancy; Welfare; Consumption (sociology); Survival analysis; Actuarial science; Economics; Proportional hazards model; Econometrics; Demography; Health and Retirement Study; Statistics; Medicine; Gerontology; Population; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.003296557,0.000255726,0.0008692308,0.00005745618,0.003584718,0.00006220533,0.0004995167,0.0002244509,0.00006829381],"category_scores_gemma":[0.0005031434,0.0002778638,0.00005932332,0.00003355496,0.0002019027,0.0003920011,0.0005579209,0.0008222997,0.0002129288],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005528494,"about_ca_system_score_gemma":0.001172678,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03962589,"about_ca_topic_score_gemma":0.06454679,"domain_scores_codex":[0.9965695,0.0006522838,0.001035719,0.0005593142,0.0001405238,0.001042682],"domain_scores_gemma":[0.9964336,0.0004966361,0.001296054,0.001002291,0.0001385172,0.000632869],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003680737,0.00002733762,0.9886966,0.001420469,0.00003891514,0.000001533749,0.001463226,0.000003771235,1.175771e-7,0.003539767,0.003880756,0.0008906741],"study_design_scores_gemma":[0.0009905838,0.00007735452,0.9854009,0.000550968,0.00001842126,0.00000137184,0.001322479,0.0002736488,0.000001456905,0.001078071,0.01007179,0.0002129138],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9772733,0.002898604,0.000008916579,0.006124234,0.002729649,0.001436453,0.0002931557,0.0001199624,0.009115677],"genre_scores_gemma":[0.9866955,0.007313968,0.0002429924,0.004961514,0.0004591662,0.00009055892,0.00007275722,0.0000380313,0.0001255125],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0249209,"threshold_uncertainty_score":0.9999673,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5855228149128477,"score_gpt":0.5377266334394931,"score_spread":0.04779618147335463,"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."}}