{"id":"W7058346563","doi":"","title":"Multi-Valued Model Checking IoT and Intelligent
\\nSystems with Trust and Commitment Protocols","year":2024,"lang":"en","type":"dissertation","venue":"Spectrum Research Repository (Concordia University)","topic":"Magnetic Field Sensors Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Concordia University","keywords":"Model checking; Context (archaeology); Reliability (semiconductor); Formal verification; Temporal logic; Internet of Things; Linear temporal logic; Description logic; Trust management (information system); Consistency (knowledge bases)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006349661,0.0006742683,0.0007266609,0.001145205,0.001343088,0.004446188,0.00243534,0.001370791,0.002787981],"category_scores_gemma":[0.01876311,0.0006288694,0.002628052,0.000943563,0.004171255,0.005224914,0.00476291,0.00379606,0.0002696223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005010422,"about_ca_system_score_gemma":0.004418936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01302973,"about_ca_topic_score_gemma":0.01200435,"domain_scores_codex":[0.9918174,0.002996696,0.0005586253,0.001295582,0.002495653,0.0008360537],"domain_scores_gemma":[0.9854525,0.009650307,0.001171437,0.001532911,0.00174925,0.000443609],"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":[0.0002113177,0.0001301212,0.001915994,0.0001501411,0.000127661,0.0005703302,0.000510738,0.3067634,0.003937046,0.6613216,0.002088087,0.02227352],"study_design_scores_gemma":[0.00004133593,0.00003544082,0.0001246187,0.00003636667,0.00003377635,0.00005757179,0.0001063483,0.7827764,0.003851465,0.2111345,0.001774048,0.00002813065],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04872417,0.0001796954,0.9420338,0.001711535,0.0001282482,0.0001411184,0.0001686505,0.0006496202,0.006263271],"genre_scores_gemma":[0.8324897,0.0001974493,0.162388,0.0005249677,0.00008121858,0.0001815895,0.0003329966,0.0001062825,0.003697837],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01302973,"threshold_uncertainty_score":0.03635335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03687699727560405,"score_gpt":0.2959814917344075,"score_spread":0.2591044944588035,"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."}}