{"id":"W130981897","doi":"10.1023/a:1025888820636","title":"Regression Modeling with Recurrent Events and Time-Dependent Interval-Censored Marker Data","year":2003,"lang":"en","type":"article","venue":"Lifetime Data Analysis","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Actua; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Statistics; Interval (graph theory); Regression analysis; Econometrics; Logistic regression; Regression; Proportional hazards model; Computer science; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02420528,0.00129076,0.002453084,0.001528128,0.0006795915,0.002594261,0.006366086,0.00290519,0.003289737],"category_scores_gemma":[0.07385012,0.0009763607,0.002098757,0.002931953,0.001733164,0.004281386,0.002019978,0.003808707,0.0006279378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007979106,"about_ca_system_score_gemma":0.001187156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004702569,"about_ca_topic_score_gemma":0.003632095,"domain_scores_codex":[0.9907313,0.006180153,0.0004478209,0.001651373,0.0005313068,0.0004580369],"domain_scores_gemma":[0.9383377,0.04973076,0.004876442,0.005413834,0.001013146,0.0006280688],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0007239504,0.0002903722,0.03099247,0.0005537933,0.001507049,0.001499766,0.001216465,0.3823001,0.0009649032,0.4966798,0.003445356,0.07982598],"study_design_scores_gemma":[0.00007348144,0.0001225841,0.002977306,0.00006442876,0.00025223,0.0002918849,0.0001149081,0.7698587,0.0003115191,0.2238156,0.002069674,0.00004762864],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03738105,0.001001228,0.9596174,0.0006590546,0.000112502,0.0000392296,0.0005030889,0.000207236,0.0004791305],"genre_scores_gemma":[0.786104,0.002674751,0.1976531,0.0003261782,0.0006004196,0.0006435679,0.002833841,0.0001717846,0.00899233],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02420528,"threshold_uncertainty_score":0.1280113,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1225561169390877,"score_gpt":0.3902947496979854,"score_spread":0.2677386327588978,"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."}}