{"id":"W3000338135","doi":"10.1098/rsos.202097","title":"Human mortality at extreme age","year":2021,"lang":"en","type":"preprint","venue":"Royal Society Open Science","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Longevity; Demography; Sampling frame; Mortality rate; Medicine; Gerontology; Population; Sociology","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","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["sts","open_science"],"category_scores_codex":[0.01180079,0.0005624135,0.0008414115,0.00009530807,0.006886391,0.005120354,0.01047209,0.0004944997,0.001746786],"category_scores_gemma":[0.0002460618,0.0006088561,0.0009446691,0.001629248,0.006346193,0.0007972936,0.02040501,0.00101536,0.00009054848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001755481,"about_ca_system_score_gemma":0.001777423,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.06922404,"about_ca_topic_score_gemma":0.03140088,"domain_scores_codex":[0.9905196,0.0005376374,0.0008005545,0.00260926,0.003929218,0.001603774],"domain_scores_gemma":[0.9957226,0.00006399247,0.0006398763,0.002333144,0.0006346913,0.0006056904],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001505332,0.001611109,0.6582999,0.0007406081,0.0009560305,0.0004683023,0.1432539,0.003135408,0.001127857,0.06880028,0.1155335,0.006058002],"study_design_scores_gemma":[0.0005441898,0.00003524798,0.9173537,0.0002759446,0.0002127498,7.197141e-7,0.0184901,0.000796893,0.0001567748,0.006608454,0.05368994,0.001835227],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7044297,0.0003160466,0.0002026375,0.0006349522,0.002138232,0.001947898,0.00005265244,0.0002044173,0.2900735],"genre_scores_gemma":[0.9725178,0.0002849681,0.003549557,0.001100494,0.0004661012,0.0002304232,0.0000682754,0.00004050078,0.0217418],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2683317,"threshold_uncertainty_score":0.9996363,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09291704062273762,"score_gpt":0.3846277642989162,"score_spread":0.2917107236761786,"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."}}