{"id":"W2124252154","doi":"10.1109/tcomm.2003.814206","title":"Iterative semi-blind multiuser detection for coded mc-cdma uplink system","year":2003,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Telecommunications link; Code division multiple access; Multiuser detection; Single antenna interference cancellation; Interference (communication); Computer science; Iterative method; Decoding methods; Algorithm; Iterative and incremental development; Electronic engineering; Telecommunications; Engineering; Channel (broadcasting)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0008590649,0.0002717945,0.0002841482,0.0003922415,0.001982778,0.0003365289,0.003217183,0.0002026055,0.00001649632],"category_scores_gemma":[0.0000461008,0.0002862628,0.0002195694,0.001243895,0.0001960012,0.0006827459,0.00002899667,0.0007955015,0.0001317941],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003810101,"about_ca_system_score_gemma":0.0001875133,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003853303,"about_ca_topic_score_gemma":0.0003301504,"domain_scores_codex":[0.9972135,0.0009233123,0.0005821055,0.0004911246,0.0003422164,0.0004477781],"domain_scores_gemma":[0.9916789,0.001872558,0.000191002,0.005415662,0.0006501678,0.0001917117],"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":[0.0004818827,0.005443693,0.00003878176,0.000289933,0.001133685,0.000005083025,0.01087953,0.1833153,0.02857194,0.4685276,0.002007191,0.2993054],"study_design_scores_gemma":[0.001730289,0.0001502696,0.00002210482,0.00009773357,0.00003162718,0.00002508545,0.0003004588,0.9431842,0.03958814,0.0004512312,0.01404462,0.0003742114],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0005302668,0.0001916407,0.9927673,0.001477516,0.0004463835,0.00132929,0.00003209738,0.0005399621,0.002685589],"genre_scores_gemma":[0.9048964,0.0002619537,0.09205712,0.0001097387,0.00001991873,0.001797151,0.00001255378,0.00003972701,0.0008054859],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9043661,"threshold_uncertainty_score":0.9999589,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06708335593216987,"score_gpt":0.3269100349250854,"score_spread":0.2598266789929155,"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."}}