{"id":"W3136525499","doi":"10.1007/s10985-021-09519-3","title":"The semiparametric accelerated trend-renewal process for recurrent event data","year":2021,"lang":"en","type":"article","venue":"Lifetime Data Analysis","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Jewish General Hospital; McGill University; McGill University Health Centre","funders":"Canadian Institutes of Health Research","keywords":"Semiparametric model; Event (particle physics); Econometrics; Process (computing); Computer science; Semiparametric regression; Event data; Renewal theory; Statistics; Covariate; Mathematics; Nonparametric statistics","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":[0.01900063,0.0009641384,0.002001159,0.002328232,0.0006127511,0.002177214,0.00298818,0.001716041,0.003584656],"category_scores_gemma":[0.07783992,0.0009050826,0.00205908,0.002265154,0.002730102,0.004355937,0.0023095,0.003551681,0.0007928235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001032813,"about_ca_system_score_gemma":0.001989075,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002419319,"about_ca_topic_score_gemma":0.001726174,"domain_scores_codex":[0.9943901,0.00335189,0.0002703759,0.0009493381,0.00075768,0.0002806227],"domain_scores_gemma":[0.9353812,0.04970046,0.004237598,0.006715899,0.003080557,0.0008842832],"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":[0.0002756773,0.0001442387,0.01140159,0.0003869825,0.0003848378,0.0003753674,0.0006012073,0.1682621,0.003016015,0.7352871,0.002864624,0.07700013],"study_design_scores_gemma":[0.00003370896,0.00009066568,0.002644908,0.00005177956,0.00008284464,0.0002168677,0.0000493588,0.7281623,0.0005258188,0.2661481,0.001953142,0.00004037918],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02947835,0.0004145881,0.9687298,0.0003554123,0.00004804541,0.00003885944,0.000248225,0.0001992787,0.0004874803],"genre_scores_gemma":[0.7524489,0.002437545,0.2316861,0.0002997692,0.0004967095,0.0006017182,0.002228194,0.0002926629,0.009508343],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01900063,"threshold_uncertainty_score":0.1004861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3311619082900739,"score_gpt":0.4953385755634719,"score_spread":0.1641766672733981,"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."}}