{"id":"W4388821093","doi":"10.1109/ats59501.2023.10318022","title":"Industry Session I: On Automotive Testing","year":2023,"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":"Microsemi (Canada)","funders":"","keywords":"Automotive industry; Session (web analytics); Quality (philosophy); Time to market; Test (biology); Test strategy; Automotive electronics; Computer science; Manufacturing engineering; Reliability engineering; Fault (geology); Engineering; Automotive engineering; Operating system","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":[0.0002172888,0.00007276092,0.00006745756,0.0001081402,0.0001572078,0.00008537395,0.0003536239,0.0001173799,0.00001333864],"category_scores_gemma":[0.0005222597,0.00005833918,0.00001969732,0.001199906,0.00001066213,0.000192202,0.0001605344,0.0003855178,0.0006270325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001831053,"about_ca_system_score_gemma":0.00004475124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001793059,"about_ca_topic_score_gemma":5.995349e-7,"domain_scores_codex":[0.9992257,0.00002612833,0.00009693165,0.0002465186,0.0001728702,0.0002318828],"domain_scores_gemma":[0.9993041,0.0003208261,0.00003361084,0.0002171429,0.00005777648,0.00006653716],"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":[5.140426e-8,0.00003760665,0.02734775,0.000008900841,0.000005611121,0.0001488684,0.0003845744,0.0017089,0.002881287,0.01871553,0.008461189,0.9402997],"study_design_scores_gemma":[0.0002911972,0.0001961431,0.1912755,0.0002883198,0.000002910234,0.00003530965,0.0002375734,0.7909226,0.00707969,0.008553075,0.000698861,0.0004188847],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5326697,0.000006890796,0.1138055,0.003664245,0.0006983949,0.0001443038,0.00000113151,0.006494058,0.3425159],"genre_scores_gemma":[0.9954484,2.089161e-7,0.00172814,0.0008953893,0.0000791178,0.000002884673,7.576834e-7,0.000005254911,0.0018399],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9398808,"threshold_uncertainty_score":0.8059443,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08204957130390911,"score_gpt":0.2930687504635943,"score_spread":0.2110191791596852,"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."}}