{"id":"W4402833001","doi":"10.1109/nss/mic/rtsd57108.2024.10657331","title":"Investigation of BGO Coincidence Time Resolution with Deep Learning","year":2024,"lang":"en","type":"article","venue":"","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Coincidence; Resolution (logic); Computer science; Artificial intelligence; Deep learning; Medicine","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":[0.0006085458,0.000383842,0.0002572116,0.0002997166,0.0001407527,0.0003605854,0.0006234132,0.0004466806,0.0007791975],"category_scores_gemma":[0.001850815,0.0001371233,0.0001877156,0.0004733424,0.0001718648,0.0006120644,0.0002985169,0.0004844691,0.0001380782],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007920023,"about_ca_system_score_gemma":0.0007987307,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006063568,"about_ca_topic_score_gemma":0.005766025,"domain_scores_codex":[0.9998583,0.0000163853,0.000004493673,0.00003566164,0.00005124832,0.00003386238],"domain_scores_gemma":[0.9995993,0.000181542,0.00005176513,0.00002715714,0.0001118467,0.00002845875],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007627244,0.0003332373,0.01936598,0.0002156738,0.0001562233,0.000280971,0.0001021112,0.5537101,0.09711852,0.005629582,0.002273726,0.3200512],"study_design_scores_gemma":[0.000003510542,0.00003984224,0.001125347,0.000003224362,0.000007599225,0.00001726394,0.000008091277,0.9862687,0.0119447,0.0002749279,0.0003033535,0.000003507423],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7954192,0.000933224,0.1972621,0.0004717084,0.00005384359,0.00002676802,0.0002956933,0.001323474,0.004214013],"genre_scores_gemma":[0.9604446,0.0002000524,0.03765243,0.00006241261,0.00001072135,0.00001166352,0.0003145343,0.0000373213,0.001266164],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006063568,"threshold_uncertainty_score":0.01205659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01184752036027113,"score_gpt":0.1976860773945084,"score_spread":0.1858385570342372,"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."}}