{"id":"W4283823758","doi":"10.1002/cjs.11711","title":"Life history analysis with multistate models: A review and some current issues","year":2022,"lang":"en","type":"review","venue":"Canadian Journal of Statistics","topic":"Birth, Development, and Health","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Theme (computing); Observational study; Selection (genetic algorithm); Process (computing); Data science; Work (physics); Life history; Computer science; Management science; History; Psychology; Risk analysis (engineering); Operations research; Medicine; Artificial intelligence; Engineering; Biology; Ecology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005830182,0.0003478106,0.003008824,0.001004882,0.0001257565,0.00002029597,0.0001683141,0.00007923444,0.0009422254],"category_scores_gemma":[0.0002940539,0.0002668132,0.000216585,0.0004053342,0.0001397104,0.00008072936,0.0000154418,0.001046631,0.000004533435],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001923552,"about_ca_system_score_gemma":0.02963594,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002096098,"about_ca_topic_score_gemma":0.007140395,"domain_scores_codex":[0.9976548,0.0001691842,0.001159577,0.0002499974,0.000386993,0.0003794389],"domain_scores_gemma":[0.9956867,0.0001031099,0.001179439,0.0002476736,0.0002799281,0.002503223],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000009189445,0.0000286243,0.00004493378,0.1209245,0.00245041,0.001407166,0.000476499,0.000002974122,7.195163e-10,0.009298039,0.2137271,0.6516306],"study_design_scores_gemma":[0.0002590982,0.000180503,0.00002492478,0.01617873,0.02074878,0.0004444843,0.00002823146,0.00003111026,5.533024e-10,0.0004284125,0.9614259,0.0002497945],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[2.103937e-7,0.9963022,0.001350985,0.0003104588,0.0003041825,0.0004573328,0.00112009,0.000004427979,0.0001501428],"genre_scores_gemma":[5.307177e-7,0.9896659,0.00821033,0.001429264,0.0001549625,0.00001584477,0.000308153,0.00005329692,0.0001617141],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.7476988,"threshold_uncertainty_score":0.9999784,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1500169234028528,"score_gpt":0.3549672639593293,"score_spread":0.2049503405564765,"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."}}