{"id":"W2151005115","doi":"10.1109/pacrim.1991.160741","title":"A technique for reducing computation in the simulation of communications systems operating on fading channels","year":2002,"lang":"en","type":"article","venue":"","topic":"Probability and Risk Models","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Simon Fraser University","keywords":"Fading; Computation; Channel (broadcasting); Computer science; Monte Carlo method; Variance (accounting); Sampling (signal processing); Algorithm; Telecommunications; Statistics; Mathematics; Detector","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002598348,0.001155059,0.0009008534,0.00116341,0.0008595408,0.0007616368,0.001374956,0.0008360493,0.003657483],"category_scores_gemma":[0.01518647,0.0008525029,0.00104439,0.000988588,0.000849854,0.001357292,0.001661072,0.002873686,0.001054223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005810499,"about_ca_system_score_gemma":0.001440786,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003518699,"about_ca_topic_score_gemma":0.004214165,"domain_scores_codex":[0.9981295,0.0008994634,0.00009402346,0.0001227799,0.0006408594,0.0001133091],"domain_scores_gemma":[0.9913892,0.00655495,0.000356123,0.001022816,0.0005301176,0.0001467489],"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":[0.0002480884,0.0002017708,0.002072916,0.0002662022,0.0001371961,0.0002415212,0.0002936447,0.6552901,0.01483192,0.08695399,0.003971494,0.2354912],"study_design_scores_gemma":[0.0000346298,0.00005722354,0.000165182,0.0000202874,0.00002621721,0.00008196283,0.000009778158,0.9709049,0.004404763,0.02027926,0.00400064,0.00001510588],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001251854,0.00003455704,0.9976152,0.00002831243,0.00001730402,0.00002835875,0.00001086554,0.0006803753,0.0003332355],"genre_scores_gemma":[0.0653807,0.0001713278,0.9329769,0.00006703983,0.00005030944,0.0003301061,0.00007986667,0.0003262193,0.0006176243],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003657483,"threshold_uncertainty_score":0.01374155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3890286185681189,"score_gpt":0.4539671946456589,"score_spread":0.06493857607754006,"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."}}