{"id":"W4405937423","doi":"10.1109/iccais63750.2024.10814271","title":"Anomaly Detection in Dynamic Power Events Using Data Fusion for Chip Design","year":2024,"lang":"en","type":"article","venue":"","topic":"VLSI and Analog Circuit Testing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Advanced Micro Devices (Canada); McMaster University","funders":"","keywords":"Anomaly detection; Chip; Computer science; System on a chip; Sensor fusion; Power (physics); Embedded system; Data mining; Artificial intelligence; Telecommunications; 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":[0.0005090534,0.00007312356,0.00006844327,0.0001421312,0.0000749949,0.000122815,0.0005015443,0.00003516104,0.00000505163],"category_scores_gemma":[0.00005990971,0.00006494999,0.00002212825,0.0003931,0.00000496334,0.000673497,0.0001952702,0.00006696433,0.00001043643],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000582551,"about_ca_system_score_gemma":0.00005812049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006444917,"about_ca_topic_score_gemma":0.0001110177,"domain_scores_codex":[0.9991624,0.00003412407,0.0001397514,0.0003849499,0.00009616952,0.0001825863],"domain_scores_gemma":[0.9994639,0.0001188063,0.00001968955,0.0003542125,0.00001564237,0.00002778168],"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":[9.377132e-7,0.00004632449,0.0008989897,0.00005662091,0.00001191976,0.0000292564,0.0002645786,0.001223419,0.09847645,0.0009434,0.00005169751,0.8979964],"study_design_scores_gemma":[0.00008257593,0.00003446945,0.002621002,0.00007243086,0.000003171675,0.00002279166,0.000009261276,0.9943614,0.0006662338,0.001979755,0.00005714492,0.00008976298],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08984254,0.0001170096,0.9092119,0.00005782727,0.0003535131,0.0001465556,0.00000221809,0.0001551378,0.0001132706],"genre_scores_gemma":[0.9722312,0.000001906194,0.02762189,0.00004328859,0.00002180405,0.000003408141,0.00000423738,0.000007500705,0.00006474626],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.993138,"threshold_uncertainty_score":0.2648584,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08861643092463771,"score_gpt":0.318515474037961,"score_spread":0.2298990431133233,"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."}}