{"id":"W2109048522","doi":"10.1109/isit.2006.261813","title":"Multiuser Detection of M-QAM Symbols via Bit-Level Equalization and Soft Detection","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Multiuser detection; Detector; Computer science; Decoding methods; Algorithm; Channel (broadcasting); Equalization (audio); Intersymbol interference; Quadrature amplitude modulation; Interference (communication); Code division multiple access; Detection theory; QAM; Bit error rate; Electronic engineering; Telecommunications; 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":[0.0009263027,0.0005405878,0.0006599714,0.0006899879,0.0003186508,0.001271655,0.0009761834,0.001066633,0.001548697],"category_scores_gemma":[0.002776689,0.0003066919,0.0006054975,0.0006958917,0.001093114,0.001435927,0.001850092,0.000942673,0.0006079461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004397008,"about_ca_system_score_gemma":0.0008562196,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004077593,"about_ca_topic_score_gemma":0.000897906,"domain_scores_codex":[0.9991497,0.0002568086,0.0000414886,0.0001053719,0.0003606073,0.00008598106],"domain_scores_gemma":[0.999202,0.0003862446,0.00008455195,0.0001603214,0.0001338313,0.0000330049],"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":[0.0001926355,0.0001207844,0.001450438,0.0002152945,0.00008902914,0.000218667,0.0003084437,0.2572749,0.05633457,0.4585618,0.001282396,0.2239511],"study_design_scores_gemma":[0.00001169751,0.00005746519,0.0002906907,0.0000191359,0.00001182248,0.0001617458,0.00001694146,0.9181513,0.01944807,0.06006529,0.001740685,0.00002505541],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005184153,0.0001034352,0.9931648,0.00006837329,0.00001659639,0.00001685345,0.00001342941,0.00005907545,0.001373305],"genre_scores_gemma":[0.3175922,0.0003784605,0.6772805,0.0002094423,0.00007226505,0.00009911752,0.00005481485,0.00003880003,0.004274327],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001548697,"threshold_uncertainty_score":0.005180955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01200168552871647,"score_gpt":0.2251199584664916,"score_spread":0.2131182729377752,"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."}}