{"id":"W2887330313","doi":"","title":"Neural Message Passing for Jet Physics","year":2017,"lang":"en","type":"article","venue":"Open Repository and Bibliography (University of Liège)","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Energy Research Scientific Computing Center; Tencent; Canadian Institute for Advanced Research; Nvidia; National Science Foundation","keywords":"Physics; Jet (fluid); Computer science; Mechanics","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.0001140891,0.0000662126,0.0001168179,0.0005576595,0.001631165,0.00051483,0.001143925,0.00004225077,0.000001628562],"category_scores_gemma":[1.058963e-7,0.00007105726,0.0001059608,0.0009692853,0.0001533363,0.001322148,0.0005108596,0.00004952485,2.826125e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002205316,"about_ca_system_score_gemma":0.00001080462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000556507,"about_ca_topic_score_gemma":0.000003400746,"domain_scores_codex":[0.9995269,0.00001799041,0.00006297715,0.0002292389,0.00007059707,0.00009228748],"domain_scores_gemma":[0.9991405,0.00002521663,0.0002035361,0.000500033,0.00007612767,0.0000545778],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001662958,0.0005484992,0.6790947,0.0001891267,0.0003049932,0.00005120877,0.0009520266,0.00001148308,0.04522548,0.1650969,0.05654573,0.05181351],"study_design_scores_gemma":[0.001982598,0.0007472457,0.8915799,0.000134902,0.0001526338,0.00005424635,0.0005442384,0.02302947,0.04413849,0.01811386,0.01864874,0.0008736717],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0838673,0.00006118391,0.9029362,0.001148349,0.0001328572,0.0004150674,0.000009983904,0.00008521871,0.01134391],"genre_scores_gemma":[0.9574463,0.00009694259,0.04210043,0.00002377622,0.00002862299,0.000001755676,7.67379e-7,0.000002642371,0.0002987583],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.873579,"threshold_uncertainty_score":0.9996686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0304546620944054,"score_gpt":0.2633017888793495,"score_spread":0.2328471267849441,"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."}}