{"id":"W2749556736","doi":"10.1177/0962280217727314","title":"Survival forests for data with dependent censoring","year":2017,"lang":"en","type":"article","venue":"Statistical Methods in Medical Research","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"Russian Science Foundation","keywords":"Censoring (clinical trials); Estimator; Covariate; Survival analysis; Computer science; Accelerated failure time model; Survival function; Statistics; Kaplan–Meier estimator; Econometrics; Data mining; Mathematics; Machine learning","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":[0.01929636,0.001154988,0.001839898,0.004022303,0.00122237,0.001843894,0.001956872,0.001673973,0.003076842],"category_scores_gemma":[0.05114826,0.0007679569,0.002631843,0.003185028,0.001739954,0.002529273,0.001937121,0.00368895,0.001041062],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008252551,"about_ca_system_score_gemma":0.001728896,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003226165,"about_ca_topic_score_gemma":0.00370673,"domain_scores_codex":[0.9915363,0.005954317,0.0004376878,0.0008579643,0.0009329809,0.0002808215],"domain_scores_gemma":[0.9431883,0.04874451,0.00215948,0.003184116,0.00225056,0.0004730851],"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":[0.0003430108,0.0001123187,0.0120117,0.001104583,0.0005424994,0.0008441167,0.0007558939,0.3543262,0.002538,0.3185531,0.009903361,0.2989653],"study_design_scores_gemma":[0.00005295426,0.00004496352,0.00175854,0.0001780998,0.00007592904,0.0002822333,0.00006785418,0.6638814,0.0006449366,0.3261619,0.006807944,0.00004337353],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002978841,0.0006087517,0.9954745,0.0001466064,0.00005026358,0.00004223819,0.0001602433,0.0002587603,0.0002797215],"genre_scores_gemma":[0.1290068,0.002218714,0.8632469,0.0003574014,0.000499556,0.0008987545,0.00185387,0.0003145504,0.001603561],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01929636,"threshold_uncertainty_score":0.1020501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6773318042169131,"score_gpt":0.6953959658900677,"score_spread":0.01806416167315461,"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."}}