{"id":"W1602205142","doi":"10.1007/11513988_24","title":"Improved Probabilistic Models for 802.11 Protocol Verification","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Formal Methods in Verification","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Federation for the Humanities and Social Sciences","keywords":"Computer science; Probabilistic logic; Reachability; Exponential backoff; Model checking; Abstraction; Protocol (science); Probabilistic CTL; Divergence-from-randomness model; Computer network; Distributed computing; Wireless; Theoretical computer science; Probabilistic analysis of algorithms; Throughput; Artificial intelligence","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":[0.00535687,0.001846718,0.00183838,0.001767074,0.001204477,0.003680977,0.005185446,0.002277526,0.01055988],"category_scores_gemma":[0.02205306,0.002025781,0.002967958,0.001588196,0.002487216,0.009074668,0.004351942,0.006131963,0.003123797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002980601,"about_ca_system_score_gemma":0.002787659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003675709,"about_ca_topic_score_gemma":0.005251015,"domain_scores_codex":[0.9901335,0.002971025,0.0007052126,0.0009984383,0.004536052,0.0006557348],"domain_scores_gemma":[0.9845461,0.008496937,0.0008130924,0.004125105,0.001778221,0.000240555],"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":[0.0003045577,0.0001263485,0.0003655979,0.0002585887,0.00009439879,0.0002113974,0.0002653198,0.3599655,0.003581362,0.5810908,0.004706467,0.04902969],"study_design_scores_gemma":[0.00004896333,0.00003947973,0.00006387466,0.00003110892,0.00005192577,0.00005587854,0.00001312102,0.7587367,0.001784613,0.2352541,0.003893362,0.00002685463],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002473909,0.0001637109,0.9927995,0.0002412181,0.00006782659,0.000090932,0.000161458,0.001014928,0.002986611],"genre_scores_gemma":[0.3653599,0.0008390315,0.6137418,0.0004250938,0.0004298029,0.001179141,0.001057498,0.0008169549,0.0161507],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01055988,"threshold_uncertainty_score":0.03532636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04303138857095064,"score_gpt":0.3083600198162897,"score_spread":0.2653286312453391,"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."}}