{"id":"W4396718193","doi":"10.3204/pubdb-2024-06000","title":"Calibration of a soft secondary vertex tagger using proton-proton collisions at $\\sqrt{s}$ = 13 TeV with the ATLAS detector","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Particle Detector Development and Performance","field":"Physics and Astronomy","cited_by":0,"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; Ministry of Education, Culture, Sports, Science and Technology; Bundesministerium für Bildung und Forschung; Natural Sciences and Engineering Research Council of Canada; Vetenskapsrådet; Horizon 2020 Framework Programme; 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; Knut och Alice Wallenbergs Stiftelse; Israel Science Foundation; 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; Istituto Nazionale di Fisica Nucleare; Ministero dell'Università e della Ricerca; Grantová Agentura České Republiky; Austrian Science Fund; U.S. Department of Energy; National Natural Science Foundation of China; European Commission; Leverhulme Trust; Fundação de Amparo à Pesquisa do Estado de São Paulo; Javna Agencija za Raziskovalno Dejavnost RS; 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; Canarie; CERN; Centres de Recerca de Catalunya; Ministerio de Ciencia e Innovación","keywords":"Atlas (anatomy); Atlas detector; Physics; Vertex (graph theory); Proton; Detector; Particle physics; Calibration; Nuclear physics; ATLAS experiment; Proton therapy; Large Hadron Collider; Optics; Mathematics; Combinatorics; Biology; Graph","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":[0.002417225,0.000685808,0.0005845761,0.0008799415,0.0004902598,0.001406474,0.001134421,0.0007552289,0.001169715],"category_scores_gemma":[0.003761182,0.0003471599,0.0003811943,0.001571426,0.0003957673,0.0006870531,0.001292572,0.0005111332,0.0006566359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008877969,"about_ca_system_score_gemma":0.0008055964,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002101652,"about_ca_topic_score_gemma":0.002127194,"domain_scores_codex":[0.9985629,0.000296544,0.0000782526,0.0004903377,0.0004410634,0.0001310213],"domain_scores_gemma":[0.9985352,0.0005822222,0.0001975478,0.0003069615,0.0002871605,0.00009091452],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.008053153,0.0009601701,0.278577,0.0004091876,0.0008467057,0.0008261467,0.0003456348,0.2901458,0.2147997,0.01180608,0.004662688,0.1885677],"study_design_scores_gemma":[0.0002058234,0.001156744,0.0698632,0.00002465725,0.0001465063,0.0009285102,0.0001090643,0.5303791,0.3884452,0.002304014,0.00632065,0.0001163728],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9100865,0.0002127047,0.0830455,0.00006596885,0.00004403434,0.00009349224,0.001472029,0.001822227,0.003157376],"genre_scores_gemma":[0.9555475,0.00007121173,0.04078502,0.00004010797,0.000008401894,0.00004280014,0.002650629,0.0001636773,0.0006906331],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002417225,"threshold_uncertainty_score":0.01278365,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03747576463035641,"score_gpt":0.1941170220922017,"score_spread":0.1566412574618453,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). 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