{"id":"W4405034454","doi":"10.3204/pubdb-2025-00045","title":"An implementation of neural simulation-based inference for parameter estimation in ATLAS","year":2024,"lang":"en","type":"preprint","venue":"White Rose Research Online (University of Leeds, The University of Sheffield, University of York)","topic":"Particle Detector Development and Performance","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"CHIST-ERA; H2020 Marie Skłodowska-Curie Actions; Institut National de Physique Nucléaire et de Physique des Particules; Agencia Nacional de Promoción Científica y Tecnológica; Fundação para a Ciência e a Tecnologia; Japan Society for the Promotion of Science; Agencia Estatal de Investigación; University of Massachusetts Amherst; Narodowa Agencja Wymiany Akademickiej; Forskningsrådet om Hälsa, Arbetsliv och Välfärd; Ministerstvo Školství, Mládeže a Tělovýchovy; National Science and Technology Council; European Social Fund; Royal Society; Centre National pour la Recherche Scientifique et Technique; European Regional Development Fund; British Columbia Knowledge Development Fund; Max-Planck-Gesellschaft; Centre National de la Recherche Scientifique; U.S. Department of Energy; Carl Tryggers Stiftelse för Vetenskaplig Forskning; Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro; Knut och Alice Wallenbergs Stiftelse; Ministerstwo Edukacji i Nauki; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Bundesministerium für Wissenschaft, Forschung und Wirtschaft; Generalitat de Catalunya; Generalitat Valenciana; Agencia Nacional de Investigación y Desarrollo; UK Research and Innovation; Istituto Nazionale di Fisica Nucleare; Ministero dell'Università e della Ricerca; Grantová Agentura České Republiky; Austrian Science Fund; Natural Sciences and Engineering Research Council of Canada; Ministry of Education, Culture, Sports, Science and Technology; Bundesministerium für Bildung und Forschung; Horizon 2020 Framework Programme; Vetenskapsrådet; National Natural Science Foundation of China; European Commission; Leverhulme Trust; Fundação de Amparo à Pesquisa do Estado de São Paulo; Science and Technology Facilities Council; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Deutsche Forschungsgemeinschaft; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Ministry of Science and Technology of the People's Republic of China; Agence Nationale de la Recherche; National Science Foundation; Baden-Württemberg Stiftung; H2020 European Research Council; Norges Forskningsråd; Alexander von Humboldt-Stiftung; TRIUMF; Danmarks Grundforskningsfond; Türkiye Enerji, Nükleer ve Maden Araştırma Kurumu; Southern Methodist University; Canarie; CERN; Centres de Recerca de Catalunya; Ministerio de Ciencia e Innovación","keywords":"Inference; Computer science; Large Hadron Collider; Statistical inference; Artificial neural network; Robustness (evolution); Higgs boson; Parameter space; Algorithm; Histogram; Convolutional neural network; Particle physics; Data mining; Artificial intelligence; Mathematics; Statistics; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002269643,0.0005934564,0.000704403,0.0007726737,0.0006686609,0.00123319,0.002366473,0.001119595,0.01227712],"category_scores_gemma":[0.009193685,0.000518256,0.0008639325,0.000774499,0.0006490162,0.001020212,0.001417323,0.001850524,0.001871872],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001152215,"about_ca_system_score_gemma":0.001957186,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01522013,"about_ca_topic_score_gemma":0.01786063,"domain_scores_codex":[0.9992751,0.0002609338,0.00004783001,0.0001351688,0.0002244553,0.00005640177],"domain_scores_gemma":[0.9979583,0.001400978,0.00008640076,0.0002121239,0.0002757306,0.00006647605],"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":[0.0002452598,0.00007353172,0.002946364,0.00009957204,0.0001447135,0.0002033853,0.0001140906,0.8529261,0.001765073,0.04773877,0.004294626,0.0894484],"study_design_scores_gemma":[0.000009793969,0.000006197678,0.00008395481,0.000004054255,0.000004521205,0.00001233856,0.000003950006,0.991661,0.0005108412,0.006847757,0.000850785,0.000004811063],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004746791,0.00005364165,0.9880373,0.0001075419,0.00004764703,0.00003528857,0.0002186332,0.004626522,0.002126571],"genre_scores_gemma":[0.2464387,0.0001201861,0.7472356,0.0002788181,0.00007131496,0.0002704309,0.0008876577,0.001172986,0.00352428],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01522013,"threshold_uncertainty_score":0.04107106,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05653086948713391,"score_gpt":0.3464492914497142,"score_spread":0.2899184219625803,"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."}}