{"id":"W2617541639","doi":"10.1145/3019612.3019827","title":"Runtime verification of LTL on lossy traces","year":2017,"lang":"en","type":"article","venue":"","topic":"Formal Methods in Verification","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Soundness; Runtime verification; Computer science; Lossy compression; TRACE (psycholinguistics); Linear temporal logic; Temporal logic; Real-time computing; Programming language; Formal verification; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004337311,0.00005760248,0.00008076079,0.00004619515,0.0001558584,0.0001157604,0.001222741,0.00003934777,0.00002339878],"category_scores_gemma":[0.0001835206,0.00004901673,0.00002681575,0.00005180044,0.00007088135,0.0006571965,0.00007616393,0.00005001548,0.000128078],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001301393,"about_ca_system_score_gemma":0.00001754244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002719524,"about_ca_topic_score_gemma":0.000001329155,"domain_scores_codex":[0.9993559,0.00003589115,0.0001515311,0.0001865833,0.000179007,0.00009108544],"domain_scores_gemma":[0.9983027,0.00003036903,0.0002158802,0.001361752,0.00006304758,0.00002624221],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000007110431,0.0000585508,0.0004839198,0.00000976436,0.000004611283,3.447383e-7,0.0002037321,0.00001962978,0.009938786,0.8661995,0.0002566218,0.1228174],"study_design_scores_gemma":[0.0002752909,0.0002043557,0.2818701,0.00002743253,0.000004467197,0.00000288546,0.00002041759,0.06665906,0.637037,0.008999982,0.004708666,0.0001903611],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1106602,0.0000160196,0.7821425,0.0008165034,0.0005237812,0.0001434708,0.000001068399,0.000101699,0.1055948],"genre_scores_gemma":[0.6408302,0.000005582683,0.3585254,0.00003339622,0.00001889769,0.000004364539,3.463857e-7,0.000002271727,0.0005795769],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8571995,"threshold_uncertainty_score":0.2272177,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04724271600627607,"score_gpt":0.3400370377423821,"score_spread":0.2927943217361061,"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."}}