{"id":"W2962865366","doi":"","title":"Benefits from Superposed Hawkes Processes","year":2017,"lang":"en","type":"article","venue":"International Conference on Artificial Intelligence and Statistics","topic":"Point processes and geometric inequalities","field":"Mathematics","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Superposition principle; Point process; Computer science; Process (computing); Class (philosophy); Point (geometry); Upper and lower bounds; Algorithm; Mathematical optimization; Artificial intelligence; Econometrics; Mathematics; Statistics; Mathematical analysis","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":[0.004076941,0.001498658,0.001777978,0.001138098,0.001019021,0.001740926,0.002110409,0.001930769,0.004962975],"category_scores_gemma":[0.01732224,0.0009131703,0.001559773,0.001034707,0.002306494,0.004951027,0.003727996,0.003053074,0.0006118862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007712782,"about_ca_system_score_gemma":0.001058462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001961354,"about_ca_topic_score_gemma":0.00130676,"domain_scores_codex":[0.9980427,0.0007293897,0.00007329693,0.0004109939,0.0005728393,0.0001707437],"domain_scores_gemma":[0.9863311,0.009618232,0.0009407068,0.001487987,0.001118385,0.0005034879],"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":[0.0002548335,0.00009909475,0.00289557,0.0002726098,0.0002177522,0.000705799,0.0003272974,0.3858846,0.008796091,0.5678537,0.002368495,0.03032413],"study_design_scores_gemma":[0.00002153395,0.00009541157,0.0005757897,0.00002237362,0.00004535808,0.0001780409,0.00006061374,0.8022104,0.00107614,0.1940309,0.001646445,0.00003702566],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03772695,0.0008146892,0.9534394,0.0005708091,0.0001149159,0.00003475412,0.0001102961,0.0002274301,0.006960708],"genre_scores_gemma":[0.8985142,0.001353825,0.09098522,0.0006306399,0.0004550094,0.0001251628,0.0002526247,0.0001999182,0.007483419],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004962975,"threshold_uncertainty_score":0.02156121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3277779055284474,"score_gpt":0.4107638946153611,"score_spread":0.08298598908691368,"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."}}