{"id":"W3084811620","doi":"10.1007/s42081-020-00088-7","title":"Analysis of cyclic recurrent event data with multiple event types","year":2020,"lang":"en","type":"article","venue":"Japanese Journal of Statistics and Data Science","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"National Center for Advancing Translational Sciences","keywords":"Predictability; Estimator; Nonparametric statistics; Gaussian process; Event (particle physics); Mathematics; Computer science; Event data; Statistics; Algorithm; Applied mathematics; Gaussian","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01312776,0.0009556563,0.001720524,0.002242407,0.0005880206,0.001655018,0.002714416,0.001170008,0.002564534],"category_scores_gemma":[0.04222147,0.0005597958,0.001942404,0.002488683,0.001011421,0.002324602,0.001358581,0.001690394,0.000354076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006414304,"about_ca_system_score_gemma":0.001213289,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002243965,"about_ca_topic_score_gemma":0.001678079,"domain_scores_codex":[0.9944596,0.002479909,0.0004486069,0.001523438,0.0007620648,0.0003263771],"domain_scores_gemma":[0.9445381,0.04532667,0.003577674,0.004248663,0.001818469,0.0004904188],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.002571488,0.0005968895,0.1008263,0.0009071461,0.002308039,0.002300065,0.0006252804,0.4111111,0.01116236,0.1364541,0.003891382,0.3272458],"study_design_scores_gemma":[0.0000284923,0.00010508,0.006257852,0.00002469828,0.0001898725,0.0002545466,0.00005595594,0.9617962,0.001197443,0.02928482,0.0007703381,0.00003474735],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.100539,0.0004241997,0.897095,0.0002218299,0.00008342027,0.00009304419,0.0005716199,0.0003252029,0.0006467712],"genre_scores_gemma":[0.8882176,0.0004060702,0.1060679,0.0001189638,0.0003365281,0.0002853055,0.002868359,0.0001133166,0.001586014],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01312776,"threshold_uncertainty_score":0.06942707,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1266690097974926,"score_gpt":0.4154319901281967,"score_spread":0.2887629803307041,"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."}}