{"id":"W2962927919","doi":"10.48550/arxiv.1506.03558","title":"Using Indexed and Synchronous Events to Model and Validate Cyber-Physical Systems","year":2015,"lang":"en","type":"article","venue":"arXiv (Cornell University)","topic":"Advanced Software Engineering Methodologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Computer science; Liveness; Event (particle physics); Semantics (computer science); Set (abstract data type); Construct (python library); Search engine indexing; Model checking; State (computer science); Linear temporal logic; Programming language; Real-time computing; Data mining; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009198321,0.001394088,0.0006487299,0.002187391,0.0007456302,0.003654805,0.002885789,0.001904743,0.003250688],"category_scores_gemma":[0.02927078,0.001004996,0.002083811,0.001167822,0.003300597,0.007216515,0.00265226,0.002078286,0.0008283933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001511675,"about_ca_system_score_gemma":0.003371845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003210868,"about_ca_topic_score_gemma":0.002773449,"domain_scores_codex":[0.98784,0.004705916,0.001915055,0.001244172,0.003887101,0.000407742],"domain_scores_gemma":[0.9749221,0.01260424,0.00255422,0.006896572,0.002681907,0.0003409412],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00020536,0.0001288964,0.002916096,0.0006569253,0.0001403634,0.001099727,0.00138559,0.267125,0.01560911,0.6333115,0.003374222,0.07404733],"study_design_scores_gemma":[0.000158266,0.0002538602,0.000475942,0.0003414241,0.0001711461,0.00049167,0.000219282,0.6763827,0.05415633,0.213249,0.05399009,0.0001103319],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005474311,0.0000669326,0.9898614,0.0000963233,0.00005843367,0.0001079492,0.0001858448,0.002600617,0.001548294],"genre_scores_gemma":[0.1646208,0.000340396,0.8301079,0.0002125747,0.00007887279,0.0005565108,0.001011378,0.0008795694,0.00219212],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009198321,"threshold_uncertainty_score":0.04864597,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2166357476053329,"score_gpt":0.2492104894822728,"score_spread":0.03257474187693982,"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."}}