{"id":"W3182314191","doi":"10.22323/1.395.0822","title":"Deep Learning Transient Detection with VERITAS","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":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; U.S. Department of Energy; Office of Science; Smithsonian Institution; National Science Foundation","keywords":"Flare; Blazar; Transient (computer programming); Cherenkov radiation; Sky; Deep learning; Range (aeronautics)","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":[],"consensus_categories":[],"category_scores_codex":[0.0001003831,0.0002431508,0.0002744864,0.00009171713,0.0001229076,0.0001537625,0.000314226,0.00003583407,0.0004095902],"category_scores_gemma":[0.00001320395,0.000236809,0.0001213212,0.0002249846,0.00008682624,0.0003641832,0.00008248387,0.0003433489,0.00002102987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006568236,"about_ca_system_score_gemma":0.0001343126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006028376,"about_ca_topic_score_gemma":0.000003246211,"domain_scores_codex":[0.9984642,0.000009698461,0.0003567931,0.0004359099,0.0004441895,0.0002892681],"domain_scores_gemma":[0.9982933,0.00002987927,0.0002829199,0.00008663572,0.001203932,0.0001033086],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000617646,0.0008646342,0.04399622,0.0001269506,0.001298658,0.00001184543,0.003604039,0.001515772,0.6486547,0.1342812,0.0003385266,0.1646898],"study_design_scores_gemma":[0.009286101,0.002005966,0.03939551,0.001203116,0.0005698436,0.00007247728,0.03011678,0.08611181,0.7253501,0.07497115,0.02791104,0.003006048],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.876252,0.00004902968,0.04694584,0.0002618004,0.0002658263,0.0001557418,0.00002614118,0.0000445527,0.07599909],"genre_scores_gemma":[0.997615,0.0000174359,0.001145351,0.00004674832,0.0002685158,0.00004310257,0.00006153863,0.00002588559,0.0007763599],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1616838,"threshold_uncertainty_score":0.9656789,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0089018877061124,"score_gpt":0.2129257043384942,"score_spread":0.2040238166323818,"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."}}