{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003690536,0.0001405816,0.0001882588,0.0002272096,0.0003546778,0.0001286416,0.0001594725,0.00005143197,0.00001454303],"category_scores_gemma":[0.00007724985,0.000120805,0.00007388106,0.0005022992,0.0003857384,0.0002029744,0.000002924628,0.000151946,0.00002735131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001700978,"about_ca_system_score_gemma":0.0001773159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003047018,"about_ca_topic_score_gemma":0.000009051956,"domain_scores_codex":[0.998746,0.00001232702,0.0002184562,0.000389579,0.0003594466,0.0002742023],"domain_scores_gemma":[0.9988527,0.00007426771,0.00006303834,0.0002883261,0.0002113435,0.0005102715],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002363795,0.007604867,0.0002223138,0.003699137,0.0002587804,0.0001786689,0.003609806,0.009671101,0.3536803,0.001495026,0.01322331,0.6039929],"study_design_scores_gemma":[0.0009743403,0.000831952,0.00009007545,0.0002271784,0.00007728735,0.0001585411,0.0002466372,0.978574,0.01657387,0.00002089582,0.002061189,0.0001639738],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.677636,0.000008844471,0.3170782,0.003275504,0.0001952228,0.0009344495,0.00004959536,0.0006518018,0.0001703735],"genre_scores_gemma":[0.9786223,0.000004726517,0.02063552,0.0003228986,0.00004557654,0.0002871049,7.683567e-7,0.00002631939,0.00005484825],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9689029,"threshold_uncertainty_score":0.4926285,"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."}}