{"id":"W2464257012","doi":"10.1007/s10985-016-9372-1","title":"$$L_1$$ L 1 splitting rules in survival forests","year":2016,"lang":"en","type":"article","venue":"Lifetime Data Analysis","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":43,"is_retracted":false,"has_abstract":false,"ca_institutions":"HEC Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Rank (graph theory); Log-rank test; Statistics; Mathematics; Hazard; Function (biology); Survival analysis; Survival function; Hazard ratio; Data mining; Computer science; Combinatorics; Biology; Confidence interval; Ecology","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":[0.0007968612,0.0001175191,0.000245294,0.0003066708,0.00008113672,0.0001725998,0.002969833,0.00004073711,0.00007280918],"category_scores_gemma":[0.0001750311,0.00008382694,0.00006516528,0.001597304,0.00004010911,0.0009638435,0.001373514,0.00006099128,0.0003746509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002650584,"about_ca_system_score_gemma":0.0000361274,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000479026,"about_ca_topic_score_gemma":0.00078615,"domain_scores_codex":[0.998336,0.00006457743,0.0003171651,0.0007406918,0.0002590893,0.0002824747],"domain_scores_gemma":[0.996595,0.0002757166,0.0001029336,0.002899118,0.00003343226,0.0000938534],"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":[0.000004182094,0.0002190473,0.2047819,0.000009280315,0.0006605296,0.00003065617,0.0001707141,0.00006649108,0.0003671256,0.04596421,0.007960404,0.7397655],"study_design_scores_gemma":[0.0004627923,0.0000182804,0.3020396,0.00004230841,0.000276836,0.000003013543,0.00003777492,0.6582153,0.0001067523,0.002631328,0.03569644,0.0004695484],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01344535,0.00005563029,0.9821507,0.002354854,0.00005388837,0.00006199903,0.001098038,0.0001065609,0.0006729384],"genre_scores_gemma":[0.4700098,0.00009208768,0.5252258,0.0002218757,0.0002776412,0.00004463414,0.002776807,0.00002314255,0.001328279],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.739296,"threshold_uncertainty_score":0.5518738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03476203151519272,"score_gpt":0.2977364447300812,"score_spread":0.2629744132148885,"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."}}