{"id":"W2897257410","doi":"10.1016/s0140-6736(18)31694-5","title":"Forecasting life expectancy, years of life lost, and all-cause and cause-specific mortality for 250 causes of death: reference and alternative scenarios for 2016–40 for 195 countries and territories","year":2018,"lang":"en","type":"article","venue":"The Lancet","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":2960,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Cancer Institute; Bill and Melinda Gates Foundation","keywords":"Life expectancy; Cause of death; Demography; Gerontology; Medicine; Environmental health; Population; Disease; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001855773,0.0005937472,0.0004287995,0.0006762345,0.0002597197,0.000718764,0.0009499762,0.001001022,0.001264849],"category_scores_gemma":[0.004246764,0.0003908124,0.001728025,0.0009286649,0.0003434889,0.0009878926,0.0005476734,0.0008967663,0.0002384778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00276452,"about_ca_system_score_gemma":0.001338462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1275103,"about_ca_topic_score_gemma":0.07614148,"domain_scores_codex":[0.9995543,0.0001991369,0.00002697421,0.0001082403,0.00003781151,0.00007356311],"domain_scores_gemma":[0.9988036,0.0006435474,0.0001809055,0.00009891441,0.0001735807,0.00009945489],"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":[0.00005131445,0.00001919576,0.02614582,0.00003137301,0.00006449373,0.00007886421,0.00009663042,0.9685565,0.0001352816,0.001494623,0.0007340754,0.002591818],"study_design_scores_gemma":[0.00002561517,0.00005448733,0.01873126,0.00004337667,0.00004730358,0.00003794449,0.0002058913,0.9767259,0.0002931327,0.002412609,0.001385559,0.0000369838],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9720008,0.0002523773,0.01419836,0.0007189499,0.00004373127,0.00005456918,0.009992794,0.0001368998,0.002601547],"genre_scores_gemma":[0.9867481,0.0001479576,0.005619694,0.00003521782,0.00001094839,0.00005739294,0.006854054,0.00001646444,0.0005101312],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1275103,"threshold_uncertainty_score":0.2535362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1714414244072864,"score_gpt":0.359808069226501,"score_spread":0.1883666448192147,"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."}}