{"id":"W4309245579","doi":"10.1038/s41592-022-01689-8","title":"Regression modeling of time-to-event data with censoring","year":2022,"lang":"en","type":"article","venue":"Nature Methods","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre","funders":"","keywords":"Censoring (clinical trials); Event data; Computer science; Regression analysis; Statistics; Regression; Event (particle physics); Computational biology; Data mining; Econometrics; Biology; 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":[0.01887519,0.001705974,0.002663461,0.001967586,0.0006604292,0.002634773,0.005800632,0.002637724,0.00547717],"category_scores_gemma":[0.06973325,0.001165564,0.002584844,0.002990036,0.002085089,0.003640953,0.002336097,0.004686985,0.001386312],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001203993,"about_ca_system_score_gemma":0.00185604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005835669,"about_ca_topic_score_gemma":0.003540343,"domain_scores_codex":[0.9907067,0.005865845,0.0004494999,0.001634484,0.0007867811,0.0005566818],"domain_scores_gemma":[0.9363149,0.05299739,0.003557745,0.005050567,0.001432219,0.0006471332],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003327697,0.0001720954,0.008172904,0.000657876,0.0008568464,0.0005377891,0.000437536,0.4312542,0.001214278,0.4980738,0.004308025,0.05398193],"study_design_scores_gemma":[0.00004008612,0.00005752403,0.001046977,0.00005766557,0.0001208983,0.0001066214,0.00003865252,0.7760715,0.0003134307,0.2198745,0.002240744,0.0000313046],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008443591,0.0006522611,0.9885216,0.000570975,0.0001460358,0.00003523062,0.000442856,0.0003296684,0.0008578321],"genre_scores_gemma":[0.7011414,0.005897635,0.2571735,0.000906641,0.001369261,0.001022712,0.004942321,0.0006396808,0.02690689],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01887519,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1560028235897252,"score_gpt":0.5006083072696969,"score_spread":0.3446054836799717,"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."}}