{"id":"W1504690257","doi":"10.1023/a:1012544714667","title":"Dynamic Random Effects Models for Times Between Repeated Events","year":2001,"lang":"en","type":"article","venue":"Lifetime Data Analysis","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Covariate; Context (archaeology); Proportional hazards model; Econometrics; Event (particle physics); Mathematics; Statistics; Random effects model; Variance (accounting); Hazard; Variance function; Regression analysis; Computer science","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":[0.001107359,0.0002270182,0.0008793076,0.0002347199,0.0001247472,0.00005434768,0.0007440678,0.0001148466,0.0003108979],"category_scores_gemma":[0.002764173,0.0001870128,0.0002331111,0.0009040177,0.00004149331,0.000222049,0.0002162447,0.0001132421,0.00003938919],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002751483,"about_ca_system_score_gemma":0.00002518718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006604676,"about_ca_topic_score_gemma":0.00002276812,"domain_scores_codex":[0.9978925,0.0002903335,0.000536861,0.0006246777,0.0003006981,0.0003549413],"domain_scores_gemma":[0.9930195,0.004959099,0.0002005108,0.001573044,0.0000937541,0.0001541184],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.002353122,0.002075034,0.05298781,0.002251584,0.0601986,0.0002253788,0.0008713254,0.0008832133,0.0006311632,0.2665102,0.05374033,0.5572722],"study_design_scores_gemma":[0.0009736844,0.00003970065,0.001059405,0.00003452273,0.005992289,0.000001140797,0.00000715955,0.4818533,0.00002551062,0.509556,0.0002432249,0.000214008],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001869474,0.00005590436,0.994588,0.0001573948,0.00003400266,0.0004331224,0.002265019,0.00009405205,0.00050304],"genre_scores_gemma":[0.08723624,0.00004068981,0.9079795,0.00004864996,0.00006746752,0.00005279731,0.003686566,0.00003261833,0.0008555035],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5570582,"threshold_uncertainty_score":0.7626162,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0671459842602265,"score_gpt":0.3946858685831534,"score_spread":0.3275398843229269,"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."}}