{"id":"W4391417631","doi":"10.48550/arxiv.2401.15330","title":"Optimal Sparse Survival Trees","year":2024,"lang":"en","type":"preprint","venue":"PubMed","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Institute on Drug Abuse; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health","keywords":"Tree (set theory); Mathematics; Combinatorics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004199796,0.0002046081,0.0002162786,0.0001159523,0.00005790053,0.000803166,0.001842926,0.0001299918,0.000005524541],"category_scores_gemma":[0.00003477986,0.0001906938,0.0001140632,0.0002424548,0.00004207495,0.00009678372,0.004737062,0.0005045416,0.0002047464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005904212,"about_ca_system_score_gemma":0.0000964608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001015933,"about_ca_topic_score_gemma":0.00001683551,"domain_scores_codex":[0.9983016,0.00002908412,0.0002257913,0.0007963445,0.0002713677,0.00037582],"domain_scores_gemma":[0.9984335,0.00005217021,0.00007478421,0.001240895,0.00004581868,0.0001528848],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[8.081e-7,0.00005095027,0.00002973895,0.00003946748,0.00005733777,0.00002335553,0.0001239273,0.0004870883,0.000001131686,0.03484474,0.01589799,0.9484435],"study_design_scores_gemma":[0.0004344232,0.00002530754,0.1005413,0.00013345,0.0001707172,0.000045183,0.00006135384,0.5013902,0.0004332855,0.06196153,0.332794,0.002009254],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04458065,0.003399922,0.8366109,0.02407938,0.01793693,0.00354099,0.001231758,0.004206683,0.06441285],"genre_scores_gemma":[0.4726489,0.0002533066,0.4812512,0.0003929473,0.002861856,0.02198366,0.0003894853,0.0001229074,0.02009567],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9464342,"threshold_uncertainty_score":0.7776268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0481242319359733,"score_gpt":0.2576262829636149,"score_spread":0.2095020510276417,"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."}}