{"id":"W4391431695","doi":"10.3390/risks12020027","title":"LSTM-Based Coherent Mortality Forecasting for Developing Countries","year":2024,"lang":"en","type":"article","venue":"Risks","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Xi’an Jiaotong-Liverpool University; Concordia University; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Life expectancy; Developing country; Benchmark (surveying); Computer science; Term (time); Econometrics; Economics; Demography; Geography; Economic growth; Population; Sociology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005615497,0.0004970974,0.0003283043,0.0005537943,0.0001732692,0.0004843756,0.0005555554,0.0004663157,0.0009488573],"category_scores_gemma":[0.001678954,0.0001967703,0.0003870779,0.000861748,0.0001579833,0.001086207,0.0004973792,0.0006765846,0.0002121631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000590662,"about_ca_system_score_gemma":0.0006165113,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0128535,"about_ca_topic_score_gemma":0.01086711,"domain_scores_codex":[0.9998817,0.00003375098,0.00001029644,0.00004070089,0.00001584222,0.00001774435],"domain_scores_gemma":[0.9997856,0.00008395538,0.00004947314,0.000017924,0.00004996056,0.00001312579],"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":[0.00007968675,0.00004422923,0.01053274,0.00006746192,0.00009701387,0.0001126356,0.0001050392,0.8563039,0.001604903,0.005278546,0.00273839,0.1230355],"study_design_scores_gemma":[0.000002590443,0.000007030052,0.001263038,0.000005918836,0.000008866967,0.000006553448,0.00001202379,0.996071,0.0002439928,0.002164798,0.0002098971,0.0000043405],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.434588,0.00151908,0.5559511,0.001256526,0.0001698705,0.0000318925,0.001590859,0.0007442082,0.004148568],"genre_scores_gemma":[0.9646091,0.0005116122,0.03252982,0.0001044656,0.00004308468,0.00002825381,0.001016141,0.00002409786,0.001133288],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0128535,"threshold_uncertainty_score":0.0255574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2039168331591975,"score_gpt":0.4229996332222281,"score_spread":0.2190828000630306,"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."}}