{"id":"W2750195634","doi":"10.22323/1.301.0595","title":"Multi-TeV Energy Resolution Studies with VERITAS","year":2017,"lang":"en","type":"preprint","venue":"Proceedings of 35th International Cosmic Ray Conference — PoS(ICRC2017)","topic":"Astrophysics and Cosmic Phenomena","field":"Physics and Astronomy","cited_by":0,"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":"Physics; Saturation (graph theory); Energy (signal processing); Resolution (logic); Gamma ray; Brightness; Spectral line; Astrophysics; Optics; Astronomy; Computer science; Artificial intelligence","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":[0.002462725,0.0005239809,0.0005692301,0.001384733,0.0004333633,0.001817675,0.00109881,0.0006610488,0.004842049],"category_scores_gemma":[0.006105277,0.0005827914,0.000585773,0.001542948,0.0003942607,0.001675128,0.001666178,0.001178795,0.0007319438],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007281372,"about_ca_system_score_gemma":0.0002888713,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001918526,"about_ca_topic_score_gemma":0.002493953,"domain_scores_codex":[0.9987476,0.0002474806,0.00007761284,0.0003125099,0.0004274152,0.0001873434],"domain_scores_gemma":[0.9940916,0.002344354,0.0009224524,0.001398893,0.001054214,0.0001885245],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.006398228,0.0005250072,0.2812316,0.002174908,0.002236196,0.004300797,0.003737424,0.05359563,0.4701696,0.02162454,0.006947628,0.1470585],"study_design_scores_gemma":[0.0002563431,0.001326273,0.4786575,0.0005478126,0.001217091,0.006532361,0.001423601,0.1065788,0.347757,0.008654815,0.04680776,0.000240607],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9456407,0.00304618,0.02992003,0.0003255788,0.00008853404,0.0000636777,0.002044917,0.0008839336,0.01798645],"genre_scores_gemma":[0.9750805,0.0004649258,0.02005274,0.0001382644,0.00005489097,0.00002301145,0.002286119,0.0004593277,0.001440196],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004842049,"threshold_uncertainty_score":0.01619822,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04779722185654848,"score_gpt":0.2968849807154221,"score_spread":0.2490877588588736,"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."}}