{"id":"W4233986389","doi":"10.1002/wcm.450","title":"Symbol error rate calculation and data pre‐distortion for 16‐QAM transmission over nonlinear memoryless satellite channels","year":2006,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; Queen's University","funders":"","keywords":"Quadrature amplitude modulation; Additive white Gaussian noise; QAM; Nonlinear distortion; Computer science; Distortion (music); Nonlinear system; Telecommunications; Topology (electrical circuits); Amplifier; Algorithm; Constellation diagram; Bit error rate; Electronic engineering; Control theory (sociology); Mathematics; White noise; Physics; Channel (broadcasting); Bandwidth (computing); Engineering","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":[0.0009606525,0.0004033604,0.0003192011,0.0003720243,0.0001615686,0.0004169748,0.0004083106,0.0003776726,0.0009640754],"category_scores_gemma":[0.002898779,0.000157705,0.0003358773,0.0002876467,0.0004483637,0.0005422503,0.0003871254,0.0003347739,0.000259746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006599532,"about_ca_system_score_gemma":0.000422771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009033358,"about_ca_topic_score_gemma":0.000657534,"domain_scores_codex":[0.999575,0.0001320625,0.00001945628,0.00003943136,0.0002038129,0.00003030614],"domain_scores_gemma":[0.9991627,0.0004780185,0.0001129196,0.0001126367,0.000122893,0.00001087501],"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":[0.000220258,0.00003946681,0.00141491,0.0001393697,0.00004161801,0.0001419671,0.00007967369,0.9109616,0.03523273,0.02652934,0.0003259016,0.02487314],"study_design_scores_gemma":[0.000003836525,0.00003859551,0.0002511818,0.000005133671,0.000004779735,0.00006616437,0.000006642843,0.9885966,0.009717895,0.001102747,0.0002022305,0.000004209261],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1692194,0.0005828502,0.8262209,0.0001300495,0.00003578527,0.00003433241,0.00007426238,0.0003158199,0.003386573],"genre_scores_gemma":[0.9330556,0.000423612,0.0647395,0.00002557884,0.00001336152,0.00003145204,0.00006199091,0.00003520412,0.001613705],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0009640754,"threshold_uncertainty_score":0.005080462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02714647621317424,"score_gpt":0.3126658029490402,"score_spread":0.285519326735866,"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."}}