{"id":"W4385305147","doi":"10.22323/1.444.1426","title":"Search for dark matter annihilation with a combined analysis of dwarf spheroidal galaxies from Fermi-LAT, HAWC, H.E.S.S., MAGIC and VERITAS","year":2023,"lang":"en","type":"article","venue":"","topic":"Dark Matter and Cosmic Phenomena","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Instituto de Astrofísica de Canarias; Institute for Cosmic Ray Research, University of Tokyo; Centre National de la Recherche Scientifique; High Energy Accelerator Research Organization; University of Tokyo; Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro; Max-Planck-Gesellschaft; Japan Society for the Promotion of Science; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Ministério da Ciência, Tecnologia, Inovações e Comunicações; Ministerio de Educación, Cultura y Deporte; Institut National de Physique Nucléaire et de Physique des Particules; Hrvatska Zaklada za Znanost; Istituto Nazionale di Fisica Nucleare; Generalitat de Catalunya; Bundesministerium für Bildung und Forschung; Office of Science; Academy of Finland; Centres de Recerca de Catalunya; Deutsche Forschungsgemeinschaft; Smithsonian Institution; U.S. Department of Energy; European Commission; Agenzia Spaziale Italiana; National Energy Research Scientific Computing Center; Agencia Estatal de Investigación; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Ministry of Education, Culture, Sports, Science and Technology; National Aeronautics and Space Administration; National Science Foundation","keywords":"Physics; Dark matter; Annihilation; Astrophysics; Galaxy; Fermi Gamma-ray Space Telescope; Dwarf galaxy; Dwarf spheroidal galaxy; MAGIC (telescope); Astronomy; Particle 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":[0.0009085697,0.0004481101,0.0004383885,0.002703406,0.0004838069,0.0005963779,0.0003378137,0.0002646958,0.001038247],"category_scores_gemma":[0.0009099139,0.0002433024,0.0006780961,0.001267548,0.0002539856,0.0001970967,0.0008518005,0.0002056832,0.0001655765],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004779056,"about_ca_system_score_gemma":0.0003981903,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008962741,"about_ca_topic_score_gemma":0.01587302,"domain_scores_codex":[0.9996279,0.00005938038,0.00001957649,0.0001142425,0.00007864597,0.0001002072],"domain_scores_gemma":[0.9988592,0.0003246297,0.0003133677,0.0001531152,0.0001464289,0.0002032013],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005620343,0.00005975243,0.9462937,0.00002298781,0.0003232466,0.0005581357,0.0001993473,0.001910429,0.03466469,0.0003814537,0.0002585916,0.0147657],"study_design_scores_gemma":[0.00002782935,0.0001324651,0.9816657,0.000004330344,0.000120104,0.0003753059,0.000115671,0.009073343,0.007733177,0.0001364731,0.0006039292,0.00001181245],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998612,0.00003445335,0.0006567739,0.000009276471,8.038248e-7,0.000005925029,0.0002794247,0.00002648469,0.0003746972],"genre_scores_gemma":[0.9974455,0.000009104402,0.001559119,0.000004976854,0.000002715698,0.000004045343,0.0008090186,0.000008289273,0.0001573322],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008962741,"threshold_uncertainty_score":0.01782113,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01278044429600216,"score_gpt":0.2419360199547385,"score_spread":0.2291555756587364,"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."}}