{"id":"W1549339412","doi":"10.4054/demres.2000.2.2","title":"Mortality statistics for the oldest-old","year":2000,"lang":"en","type":"article","venue":"Demographic Research","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Demography; Mortality rate; Data quality; Geography; Statistics; Population; Economics; Economy; Mathematics; Sociology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001376293,0.0003613139,0.0003388783,0.01063303,0.0009851585,0.0006368847,0.0007833836,0.0001646861,0.002306951],"category_scores_gemma":[0.005209269,0.0001127145,0.0005753419,0.007530736,0.000178561,0.000293221,0.0004113027,0.0004770701,0.0004429342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009584923,"about_ca_system_score_gemma":0.01328592,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.9711893,"about_ca_topic_score_gemma":0.9718518,"domain_scores_codex":[0.9989858,0.00004959904,0.00009491892,0.00006779668,0.0006188629,0.0001829209],"domain_scores_gemma":[0.9940451,0.0002971278,0.0005426419,0.0001826157,0.004532324,0.0004001455],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002796327,0.0000510806,0.7808439,0.0007641975,0.0002955925,0.000134108,0.00126421,0.004454779,0.001009066,0.009912197,0.0871347,0.1138567],"study_design_scores_gemma":[0.00001164907,0.00003225286,0.9292179,0.00009968955,0.00005791496,0.0001484965,0.0002850289,0.0009145002,0.0003434794,0.0002901011,0.06856809,0.00003102834],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.3225212,0.01091342,0.005020617,0.001024577,0.0002884887,0.0001907662,0.6221052,0.0007102452,0.03722538],"genre_scores_gemma":[0.5977731,0.008030916,0.005296324,0.000286742,0.0001131377,0.0001439249,0.3747146,0.00007409045,0.01356708],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9711893,"threshold_uncertainty_score":0.06954378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.141334792977701,"score_gpt":0.4569539540480254,"score_spread":0.3156191610703244,"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."}}