{"id":"W3125870306","doi":"10.1007/978-3-030-67220-1_21","title":"A Semantic-Aware, Accurate and Efficient API for (Co-)Simulation of CPS","year":2021,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Embedded Systems Design Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Safran Electronics (Canada)","funders":"","keywords":"Computer science; Debugging; Semantics (computer science); Application programming interface; Interface (matter); Event (particle physics); Programming language; Simple (philosophy); Isolation (microbiology); Distributed computing; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001280774,0.0004338109,0.0006824237,0.0007307396,0.000156751,0.0003647961,0.001667796,0.0003262025,0.00000404724],"category_scores_gemma":[0.0001502221,0.0004067205,0.0001332624,0.0004712855,0.0004285244,0.0003113583,0.0007567405,0.0003412389,0.000002481862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001557238,"about_ca_system_score_gemma":0.0004162363,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001239071,"about_ca_topic_score_gemma":0.00001403919,"domain_scores_codex":[0.9966123,0.0000566306,0.000714573,0.001372882,0.0007797529,0.0004638712],"domain_scores_gemma":[0.9964062,0.00117883,0.0005111986,0.001234082,0.0005546932,0.0001149901],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002065378,0.00008260879,0.00006296566,0.0008494455,0.00004334474,0.00007521307,0.002296546,0.525764,0.002880215,0.06176676,0.00004800959,0.4061102],"study_design_scores_gemma":[0.0002164109,0.0001717571,0.00002697634,0.0007274416,0.000008925829,0.00003578397,2.508935e-7,0.9547821,0.01246158,0.03090191,0.0002544422,0.0004124399],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0002202728,0.0005254093,0.9969476,0.0001399409,0.0005773859,0.0009589198,0.00001108638,0.0001638372,0.0004555103],"genre_scores_gemma":[0.6442534,0.00002291249,0.3551017,0.0002448866,0.0001711492,0.00002440759,0.000006043496,0.00003412491,0.0001413351],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6440332,"threshold_uncertainty_score":0.9998385,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03308390282301867,"score_gpt":0.3012821929743827,"score_spread":0.2681982901513641,"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."}}