{"id":"W2962978902","doi":"10.22323/1.358.0692","title":"Proving the outstanding capabilities of Imaging Atmospheric Cherenkov Telescopes in high time resolution optical astronomy","year":2019,"lang":"en","type":"article","venue":"Proceedings of 36th International Cosmic Ray Conference — PoS(ICRC2019)","topic":"Gamma-ray bursts and supernovae","field":"Physics and Astronomy","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; National Energy Research Scientific Computing Center; U.S. Department of Energy; Office of Science; Smithsonian Institution; National Science Foundation","keywords":"Exoplanet; Cherenkov radiation; Physics; Observatory; Telescope; Stars; Astronomy; Cherenkov Telescope Array; Angular resolution (graph drawing); Photometer; Field of view; Optics; Astrophysics; Detector","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":[0.0004690443,0.0002552518,0.0004106356,0.00007365119,0.00005511602,0.0001307239,0.0006377597,0.00004760982,0.0008883905],"category_scores_gemma":[0.000043218,0.0002044223,0.0001268993,0.0001636016,0.0002080108,0.0005755508,0.0001747873,0.0003020725,0.00003632537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001217777,"about_ca_system_score_gemma":0.0001747744,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007122402,"about_ca_topic_score_gemma":0.000003897442,"domain_scores_codex":[0.9981439,0.0000143734,0.0006661272,0.0003880859,0.0004258417,0.0003617443],"domain_scores_gemma":[0.9987013,0.0001185479,0.0003636465,0.0001354597,0.000624618,0.00005647732],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000120233,0.000140578,0.8927906,0.0000832201,0.0001019253,2.9832e-7,0.001223093,0.0001535776,0.04701135,0.04798495,0.0001681761,0.01022201],"study_design_scores_gemma":[0.008840824,0.0008429859,0.7318745,0.00381655,0.0002535745,0.00002016863,0.040616,0.06218832,0.1121285,0.02529033,0.01161034,0.002517927],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9765322,0.00004907485,0.001608826,0.0005926878,0.0002005853,0.0004918876,0.00003625033,0.00002214189,0.0204664],"genre_scores_gemma":[0.9937156,0.000004406164,0.004784347,0.00001950655,0.0001413536,0.0000409032,0.00002228934,0.00002462021,0.001246956],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1609161,"threshold_uncertainty_score":0.9727253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007738327528662149,"score_gpt":0.2159701197947813,"score_spread":0.2082317922661192,"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."}}