{"id":"W2791076467","doi":"10.18154/rwth-2020-10292","title":"Computational Techniques for the Analysis of Small Signals in High-Statistics Neutrino Oscillation Experiments","year":2018,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Neutrino Physics Research","field":"Physics and Astronomy","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Japan Society for the Promotion of Science; Deutsches Elektronen-Synchrotron; Science and Technology Facilities Council; Natural Sciences and Engineering Research Council of Canada; Office of Polar Programs; College of Engineering, Michigan State University; Institute for Global Prominent Research, Chiba University; RWTH Aachen University; Chiba University; Knut och Alice Wallenbergs Stiftelse; Villum Fonden; National Research Foundation of Korea; Fonds Wetenschappelijk Onderzoek; Marsden Fund; Bundesministerium für Bildung und Forschung; Helmholtz Alliance for Astroparticle Physics; Danmarks Grundforskningsfond; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation; Belgian Federal Science Policy Office; Deutsche Forschungsgemeinschaft; Michigan State University; National Research Foundation; Western Canada Research Grid; Fonds De La Recherche Scientifique - FNRS; Polarforskningssekretariatet; Compute Canada; Marquette University; University of Wisconsin-Madison; U.S. Department of Energy; Vetenskapsrådet","keywords":"Monte Carlo method; Weighting; Neutrino; Smoothing; Sensitivity (control systems); Event (particle physics); Neutrino oscillation; Rare events; Computer science; Statistical physics; Oscillation (cell signaling); Physics; Particle physics; Statistics; Mathematics; Engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002182965,0.0001894259,0.0003739341,0.0004659302,0.0000916195,0.00003775275,0.0004994291,0.00008105626,0.0001072376],"category_scores_gemma":[0.000002129239,0.0001888727,0.0002195124,0.0007959712,0.0001482872,0.00005932918,0.0004210154,0.0002298225,0.000004478864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001027708,"about_ca_system_score_gemma":0.0001474013,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001029612,"about_ca_topic_score_gemma":0.00003643113,"domain_scores_codex":[0.9988473,0.0001003413,0.0002583068,0.0004707871,0.0001068638,0.000216381],"domain_scores_gemma":[0.9982354,0.0005735456,0.0003094353,0.0004203202,0.000412774,0.00004853475],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000711851,0.0001647725,0.04025609,0.00003179961,0.0009708084,0.000001760287,0.0000966701,0.728818,0.0001181632,0.2287489,0.0000746498,0.0006471845],"study_design_scores_gemma":[0.0007379683,0.00007653113,0.03173651,0.00005490769,0.0009857323,2.980489e-8,0.0001521965,0.8319019,0.01186931,0.1220256,0.00007294505,0.0003863535],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4176962,0.000005868294,0.580324,0.00001133939,0.00004855178,0.0005798924,0.0006712367,0.00001467168,0.0006482517],"genre_scores_gemma":[0.9973503,0.000006678922,0.00185679,0.000006696779,0.00009403603,0.00001187126,0.0004855106,0.00001662992,0.0001714521],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5796542,"threshold_uncertainty_score":0.7702006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09495810658698527,"score_gpt":0.2687669988834023,"score_spread":0.1738088922964171,"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."}}