{"id":"W3179742502","doi":"10.22323/1.395.1073","title":"The SkyLLH framework for IceCube point-source search","year":2021,"lang":"en","type":"article","venue":"Proceedings of 37th International Cosmic Ray Conference — PoS(ICRC2021)","topic":"Astrophysics and Cosmic Phenomena","field":"Physics and Astronomy","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Office of Experimental Program to Stimulate Competitive Research; Deutsches Elektronen-Synchrotron; College of Engineering, Michigan State University; Helmholtz Alliance for Astroparticle Physics; RWTH Aachen University; Vetenskapsrådet; Knut och Alice Wallenbergs Stiftelse; Fonds Wetenschappelijk Onderzoek; Deutsche Forschungsgemeinschaft; Belgian Federal Science Policy Office; Bundesministerium für Bildung und Forschung; Office of Polar Programs; Fonds De La Recherche Scientifique - FNRS; Polarforskningssekretariatet; Science and Technology Facilities Council; Michigan State University; Marquette University; University of Wisconsin-Madison; U.S. Department of Energy; National Science Foundation","keywords":"Python (programming language); Computer science; Point source; Point (geometry); Kernel density estimation; Modular design; Data mining; Physics; Statistics; Mathematics; Programming language","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":[0.002518685,0.001428467,0.001524969,0.001387704,0.0007586795,0.002862681,0.005515025,0.001256008,0.05347074],"category_scores_gemma":[0.005524406,0.001142973,0.002571314,0.001475903,0.0009829837,0.00254442,0.003327767,0.003185948,0.02968873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001136933,"about_ca_system_score_gemma":0.002352766,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007805387,"about_ca_topic_score_gemma":0.009266792,"domain_scores_codex":[0.9989586,0.0002343579,0.00007450295,0.0001414135,0.0004795156,0.0001115244],"domain_scores_gemma":[0.9988179,0.0004613839,0.00006743195,0.000299127,0.0002544077,0.00009981729],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007171357,0.0002011812,0.004165224,0.001503789,0.0004865285,0.0007030246,0.0005464207,0.1550904,0.007568321,0.1375039,0.5206063,0.1709077],"study_design_scores_gemma":[0.0004876805,0.00005037938,0.00122266,0.0001671454,0.00004958607,0.0002761048,0.00008827693,0.4964669,0.006919206,0.1746382,0.3195031,0.0001307502],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00180243,0.0003599376,0.781477,0.0003455651,0.0001958893,0.0002324681,0.02426737,0.1779373,0.01338208],"genre_scores_gemma":[0.04876183,0.0006695976,0.7787403,0.00091479,0.0002174728,0.002545913,0.07640704,0.08176081,0.009982258],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05347074,"threshold_uncertainty_score":0.1788775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0193264740449437,"score_gpt":0.2729767583462603,"score_spread":0.2536502843013166,"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."}}