{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001187501,0.0002814682,0.0002731631,0.0001080562,0.0002443683,0.00006291037,0.0003345513,0.0001102654,0.0003870227],"category_scores_gemma":[0.000002440159,0.0002186244,0.0001484748,0.0004088606,0.0001384106,0.0001602022,0.0006737142,0.0005006301,0.00003937457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001280422,"about_ca_system_score_gemma":0.0004501208,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002729978,"about_ca_topic_score_gemma":0.00004953048,"domain_scores_codex":[0.9988663,0.00006311137,0.0001965041,0.00050119,0.0001064468,0.0002665054],"domain_scores_gemma":[0.9990831,0.00006316046,0.0002286121,0.0004471233,0.00009262189,0.00008537449],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001935324,0.0004421129,0.579174,0.002445791,0.002354146,0.0001909442,0.004390314,0.3532652,0.04571709,0.006636771,0.001097206,0.002351163],"study_design_scores_gemma":[0.001101507,0.0001219936,0.002916915,0.0005403499,0.0003822462,0.000002524544,0.0003358708,0.7493508,0.2395394,0.003317717,0.001629931,0.0007607319],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9932108,0.00003027268,0.004128546,0.00002715213,0.0001658319,0.001457919,0.0001144272,0.00004807774,0.0008169822],"genre_scores_gemma":[0.9988209,0.000004352471,0.00006829198,0.000007102901,0.00007871407,0.00002783012,0.00004071343,0.00003082884,0.000921239],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5762571,"threshold_uncertainty_score":0.8915246,"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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