{"id":"W2007231971","doi":"10.1007/s10985-005-7218-3","title":"Inference for the Dependent Competing Risks Model with Masked Causes of Failure","year":2006,"lang":"en","type":"article","venue":"Lifetime Data Analysis","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":44,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Identifiability; Inference; Estimator; Statistical inference; Econometrics; Hazard; Piecewise; Computer science; Statistical model; Statistics; Mathematics; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002505365,0.00009360428,0.0002209654,0.00005543446,0.0001479871,0.00004040083,0.0004109349,0.00003096124,0.0001453724],"category_scores_gemma":[0.0005184863,0.00006066197,0.00005592139,0.0004661147,0.00008276303,0.0000701578,0.00008574167,0.00005796982,0.000007471994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001151887,"about_ca_system_score_gemma":0.00003469101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002604995,"about_ca_topic_score_gemma":0.0007591706,"domain_scores_codex":[0.9990868,0.00002698803,0.0003247417,0.000216746,0.0002256616,0.0001190692],"domain_scores_gemma":[0.9972109,0.001539638,0.0002148283,0.000834016,0.000168622,0.00003201308],"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":[0.00002254954,0.0002302365,0.003476821,0.00006373308,0.0008861512,3.914282e-7,0.00005166031,0.08864604,0.0001698625,0.8989395,0.007149648,0.0003633366],"study_design_scores_gemma":[0.0001933911,0.00000651159,0.003316027,0.000008116596,0.002314261,3.758321e-7,0.0001122975,0.9754697,0.0001479086,0.01811345,0.0002298277,0.00008810388],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002326959,0.00001039491,0.9877338,0.0006010719,0.000002266851,0.0002098427,0.008928956,0.00003087737,0.0001557657],"genre_scores_gemma":[0.8334572,0.000002181548,0.1626155,0.00002621013,0.00001459011,0.00005119186,0.003707323,0.000006566921,0.0001192693],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8868237,"threshold_uncertainty_score":0.2473723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1414265847111921,"score_gpt":0.4062468731911084,"score_spread":0.2648202884799163,"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."}}