{"id":"W4411882452","doi":"10.1080/00031305.2025.2526545","title":"LASSO-Based Survival Prediction Modeling with Multiply Imputed Data: A Case Study in Tuberculosis Mortality Prediction","year":2025,"lang":"en","type":"article","venue":"The American Statistician","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Centre for Disease Control; St. Paul's Hospital; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; University of British Columbia","keywords":"Lasso (programming language); Statistics; Econometrics; Mathematics; Computer science; Data mining","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":[0.02969929,0.0007495229,0.001584938,0.0009910756,0.001111298,0.001672655,0.001789077,0.002919602,0.001721239],"category_scores_gemma":[0.05574974,0.0005197141,0.001890205,0.002177807,0.001293657,0.001597313,0.001537429,0.003691495,0.0002490138],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001164646,"about_ca_system_score_gemma":0.001573525,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008855387,"about_ca_topic_score_gemma":0.008258117,"domain_scores_codex":[0.9877378,0.01008994,0.0003202392,0.0006874728,0.0008279912,0.0003365378],"domain_scores_gemma":[0.9375172,0.05491586,0.002061067,0.002618373,0.002170674,0.0007166542],"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":[0.001365451,0.0009887542,0.1107064,0.0004628988,0.0006759654,0.005147449,0.001245972,0.7572975,0.001041568,0.03533066,0.01242045,0.07331699],"study_design_scores_gemma":[0.0001569696,0.0003772612,0.006128774,0.00008287527,0.00009773664,0.0006917152,0.0003654002,0.9743401,0.001014328,0.01415193,0.002523804,0.00006903816],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6750761,0.001963051,0.3064648,0.01082627,0.000176475,0.0002965918,0.001299501,0.0004019765,0.003495321],"genre_scores_gemma":[0.8766139,0.000451501,0.1202529,0.0005156751,0.0001385728,0.0002665297,0.0007014223,0.0000790658,0.0009805467],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.02969929,"threshold_uncertainty_score":0.1570668,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05416784748200714,"score_gpt":0.3684578644543723,"score_spread":0.3142900169723651,"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."}}