{"id":"W2116687312","doi":"10.1109/tns.2015.2425794","title":"Automatic Channel Fault Detection and Diagnosis System for a Small Animal APD-Based <newline/>Digital PET Scanner","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Nuclear Science","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Fault detection and isolation; Scanner; Channel (broadcasting); Computer science; Calibration; Fault (geology); Sensitivity (control systems); Artificial intelligence; Real-time computing; Electronic engineering; Computer vision; Engineering; Physics","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":[0.0007824494,0.0004784081,0.0006027668,0.001073333,0.0005159601,0.0006098964,0.001128615,0.0006154959,0.005567366],"category_scores_gemma":[0.001108706,0.0003143151,0.0002483875,0.0003710682,0.0003490973,0.0005865649,0.0004573966,0.0004176168,0.001411888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009239946,"about_ca_system_score_gemma":0.001099069,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001848291,"about_ca_topic_score_gemma":0.00218796,"domain_scores_codex":[0.9995814,0.00004437684,0.00003575876,0.0001524805,0.0001484821,0.00003756055],"domain_scores_gemma":[0.9990219,0.0002199325,0.0001422931,0.0001334845,0.0003951154,0.00008718976],"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":[0.001546137,0.0004197901,0.0177904,0.0004829751,0.00009589522,0.0008983386,0.0003834178,0.01291603,0.530026,0.001830406,0.01476724,0.4188434],"study_design_scores_gemma":[0.000318775,0.001437528,0.02317875,0.00008997577,0.000305535,0.002368423,0.0001196855,0.5537916,0.3844624,0.001082466,0.03263464,0.0002101015],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1629186,0.0004772203,0.7859904,0.0007371847,0.0002325259,0.0007653678,0.000839043,0.04335107,0.004688415],"genre_scores_gemma":[0.7088018,0.0001473379,0.283514,0.0005620175,0.00005878011,0.0004892513,0.0006776061,0.000244869,0.005504335],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005567366,"threshold_uncertainty_score":0.01862472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03340748099930307,"score_gpt":0.2787553977263881,"score_spread":0.245347916727085,"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."}}