{"id":"W4319791103","doi":"10.17182/hepdata.87256","title":"Measurement of prompt photon production in $\\sqrt{s_\\mathrm{NN}} = 8.16$ TeV $p$+Pb collisions with ATLAS","year":2019,"lang":"en","type":"dataset","venue":"OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)","topic":"Particle physics theoretical and experimental studies","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"H2020 Marie Skłodowska-Curie Actions; Royal Society; Centre National pour la Recherche Scientifique et Technique; European Social Fund; European Regional Development Fund; Max-Planck-Gesellschaft; Centre National de la Recherche Scientifique; British Columbia Knowledge Development Fund; Fundação para a Ciência e a Tecnologia; Institut National de Physique Nucléaire et de Physique des Particules; Agencia Nacional de Promoción Científica y Tecnológica; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Science and Technology Facilities Council; Bundesministerium für Bildung und Forschung; Ministry of Education, Culture, Sports, Science and Technology; Natural Sciences and Engineering Research Council of Canada; Japan Society for the Promotion of Science; National Research Center \"Kurchatov Institute\"; Israel Science Foundation; Comisión Nacional de Investigación Científica y Tecnológica; Türkiye Atom Enerjisi Kurumu; Joint Institute for Nuclear Research; Ministerstwo Edukacji i Nauki; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Bundesministerium für Wissenschaft, Forschung und Wirtschaft; 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; Deutsche Forschungsgemeinschaft; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Agence Nationale de la Recherche; Services Fédéraux des Affaires Scientifiques, Techniques et Culturelles; Generalitat de Catalunya; Department of Science and Technology, Ministry of Science and Technology, India; General Secretariat for Research and Technology; National Science Foundation; Compute Canada; Alexander von Humboldt-Stiftung; TRIUMF; Departamento Administrativo de Ciencia, Tecnología e Innovación (COLCIENCIAS); Canarie; Centres de Recerca de Catalunya; CERN; Danmarks Grundforskningsfond","keywords":"Production (economics); Computer science; Artificial intelligence; Mathematics","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":[0.0007619072,0.001066111,0.0007900794,0.001494177,0.000579612,0.001190473,0.001543022,0.001010439,0.005281143],"category_scores_gemma":[0.002165361,0.0003444269,0.0008719578,0.002446624,0.0003377538,0.0007023859,0.001324547,0.0009521944,0.008420436],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009529432,"about_ca_system_score_gemma":0.0009416474,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01571906,"about_ca_topic_score_gemma":0.02535515,"domain_scores_codex":[0.9994179,0.00007693314,0.00004784907,0.0001868159,0.0001692625,0.0001011394],"domain_scores_gemma":[0.9991021,0.0002075087,0.0001662215,0.000210269,0.0002307226,0.00008318103],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001746269,0.0003360415,0.09855422,0.002438181,0.0005813204,0.000709817,0.0001940228,0.00806403,0.006221917,0.004628057,0.8541848,0.02234137],"study_design_scores_gemma":[0.000531206,0.0001401926,0.1966396,0.0002695965,0.0002299554,0.0008060421,0.0002940207,0.006707847,0.01048782,0.00408777,0.7796668,0.0001391983],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01706249,0.0003585791,0.000398819,0.0001453122,0.00004063134,0.00002267526,0.9787138,0.0005295572,0.002728199],"genre_scores_gemma":[0.01543691,0.0001408388,0.001039432,0.00006200156,0.00001653108,0.0000615528,0.9821097,0.00006228431,0.001070919],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01571906,"threshold_uncertainty_score":0.03125513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01479949665121838,"score_gpt":0.2400078772694227,"score_spread":0.2252083806182043,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). 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