{"id":"W4283739058","doi":"10.1109/ets54262.2022.9810365","title":"ETS 2022 Panel Discussion","year":2022,"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":"Siemens (Canada)","funders":"","keywords":"Automatic test pattern generation; Mixed-signal integrated circuit; Task (project management); Computer science; Computer engineering; Selection (genetic algorithm); Algorithm; Fault (geology); State (computer science); Electronic circuit; Digital electronics; Estimation; Theoretical computer science; Integrated circuit; Machine learning; Engineering; Electrical engineering; Systems engineering","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":[0.0001972317,0.00004706622,0.00005041143,0.00004297511,0.0003602095,0.00004743238,0.0005742089,0.00000704364,0.0004257175],"category_scores_gemma":[0.00001598957,0.00003024619,0.00003119611,0.0003008989,0.000006187396,0.0001495305,0.0005845706,0.000113694,0.00004499208],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002389609,"about_ca_system_score_gemma":0.00002774479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002006623,"about_ca_topic_score_gemma":0.000001829547,"domain_scores_codex":[0.9992945,0.00004664995,0.00008149423,0.0001975173,0.0002269425,0.0001529337],"domain_scores_gemma":[0.9996489,0.00002652263,0.00002502683,0.0002466647,0.000008592244,0.00004427038],"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":[6.17566e-8,0.00005630527,0.002671489,0.000002650245,0.00000307551,0.00004766597,0.0005679923,0.0002718336,0.003476391,0.04503595,0.008601155,0.9392654],"study_design_scores_gemma":[0.0009607736,0.0004518007,0.02160141,0.00001825414,0.000009701027,0.0004616843,0.001605555,0.707342,0.002110076,0.04598824,0.2183298,0.001120734],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02288494,0.0001331505,0.8740337,0.0112694,0.001128153,0.0001404457,0.000003022173,0.0009061595,0.08950105],"genre_scores_gemma":[0.9922501,7.907049e-7,0.000760806,0.0008256413,0.00003104567,0.00001104988,0.000001766067,0.000003235017,0.00611551],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9693652,"threshold_uncertainty_score":0.4661308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03453987174596114,"score_gpt":0.2360527614157173,"score_spread":0.2015128896697562,"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."}}