{"id":"W4406799269","doi":"10.1140/epjc/s10052-024-13606-8","title":"Measurement of multidifferential cross sections for dijet production in proton–proton collisions at $$\\sqrt{s} = 13\\,\\text {Te}\\hspace{-.08em}\\text {V} $$","year":2025,"lang":"en","type":"article","venue":"The European Physical Journal C","topic":"Particle physics theoretical and experimental studies","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Particle Physics","funders":"Institut National de Physique Nucléaire et de Physique des Particules; Agencia Estatal de Investigación; Fonds pour la Formation à la Recherche dans l’Industrie et dans l’Agriculture; Science and Technology Facilities Council; Qatar National Research Fund; Ministry of Science,Technology and Research; Latvijas Zinātnes Padome; European Regional Development Fund; Centre National de la Recherche Scientifique; Türkiye Enerji, Nükleer ve Maden Araştırma Kurumu; National Academy of Sciences of Ukraine; U.S. Department of Energy; Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro; Ministry of Education, India; Benemérita Universidad Autónoma de Puebla; Türkiye Bilimsel ve Teknolojik Araştırma Kurumu; Alexander von Humboldt-Stiftung; Secretaría de Educación Superior, Ciencia, Tecnología e Innovación; Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul; National Natural Science Foundation of China; National Science and Technology Development Agency; A.G. Leventis Foundation; Fundamental Research Funds for the Central Universities; Fonds Wetenschappelijk Onderzoek; Ministry of Science, ICT and Future Planning; Fonds De La Recherche Scientifique - FNRS; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Bulgarian National Science Fund; Bundesministerium für Bildung und Forschung; Ministerio de Economía y Competitividad; Ministry of Higher Education, Science, Research and Innovation, Thailand; Nvidia; Agentschap voor Innovatie door Wetenschap en Technologie; Austrian Science Fund; Ministerstvo Školství, Mládeže a Tělovýchovy; Fundação para a Ciência e a Tecnologia; Universidad Autónoma de San Luis Potosí; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; European Commission; Fundação de Amparo à Pesquisa do Estado de São Paulo; Hellenic Foundation for Research and Innovation; Department of Science and Technology, Ministry of Science and Technology, India; Nemzeti Kutatási Fejlesztési és Innovációs Hivatal; Shota Rustaveli National Science Foundation; Science Foundation Ireland; National Science Foundation; Belgian Federal Science Policy Office; Deutsche Forschungsgemeinschaft; Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional; CERN; Weston Havens Foundation; Magyar Tudományos Akadémia; National Science Council; Pakistan Atomic Energy Commission; Fonds National de la Recherche Luxembourg; Alfred P. Sloan Foundation","keywords":"Algorithm; Physics; Computer science","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":[0.002393439,0.0007978403,0.0004986542,0.002577788,0.0007664622,0.001082537,0.0009646179,0.0006221688,0.008633699],"category_scores_gemma":[0.001267736,0.000671578,0.0005575035,0.001811059,0.0004360111,0.0006126077,0.001144709,0.0008206755,0.001259468],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00111901,"about_ca_system_score_gemma":0.0004334123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001222877,"about_ca_topic_score_gemma":0.001778623,"domain_scores_codex":[0.9991432,0.0001959465,0.00003722439,0.0002355034,0.0002522018,0.0001359008],"domain_scores_gemma":[0.9987238,0.0005500096,0.0002138027,0.0001477904,0.0001819251,0.0001825902],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.008621848,0.0008911442,0.08965414,0.0004719287,0.0008739029,0.003102095,0.0005671565,0.0180451,0.8326528,0.01853321,0.005273393,0.02131334],"study_design_scores_gemma":[0.000303671,0.0009239136,0.1404355,0.00004321473,0.0001768795,0.001005314,0.0001537889,0.02593204,0.8211814,0.002544844,0.007050744,0.0002486573],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.953745,0.001199287,0.02003218,0.0002567289,0.00008269527,0.0000843673,0.005099359,0.0007362069,0.01876416],"genre_scores_gemma":[0.9929744,0.0001956234,0.002221426,0.00006501727,0.00001932488,0.00003893642,0.001959882,0.0001062301,0.002419168],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008633699,"threshold_uncertainty_score":0.02888262,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02469809417427079,"score_gpt":0.3062358121716933,"score_spread":0.2815377179974225,"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."}}