{"id":"W2123574520","doi":"10.1109/wcnc.2005.1424518","title":"Diversity combining options for spread spectrum OFDM systems in frequency selective channels","year":2005,"lang":"en","type":"article","venue":"","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Diversity scheme; Orthogonal frequency-division multiplexing; Fading; Diversity combining; Subcarrier; Computer science; Time diversity; Bit error rate; Electronic engineering; Equalization (audio); Maximal-ratio combining; Orthogonality; Interleaving; Algorithm; Channel (broadcasting); Telecommunications; Mathematics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006221577,0.0001020301,0.0001621245,0.0002209749,0.0005983926,0.0001313447,0.001606006,0.00006582888,0.00001067432],"category_scores_gemma":[0.00004039562,0.0001041909,0.0000475314,0.0007051364,0.00004111432,0.0006835859,0.001593822,0.0002291377,0.00003914942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000280762,"about_ca_system_score_gemma":0.00007592315,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009580342,"about_ca_topic_score_gemma":0.0007326975,"domain_scores_codex":[0.9986668,0.0001611303,0.0002125187,0.0003066499,0.0002505095,0.0004024237],"domain_scores_gemma":[0.9987043,0.0003539162,0.00006181647,0.0006633659,0.0001276681,0.00008894345],"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":[0.000007698577,0.0002179202,0.004410614,0.00001607487,0.0000275194,0.000002303841,0.002742071,0.03337317,0.0001319438,0.9543716,0.001691707,0.003007432],"study_design_scores_gemma":[0.0006332521,0.00008920295,0.003832252,0.00003964641,0.000001653808,0.00000597629,0.0001256964,0.9847465,0.0003420748,0.009240565,0.0007482348,0.0001949452],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03363524,0.0005699536,0.9453218,0.006480831,0.0003080353,0.001059607,0.000003843686,0.000292181,0.01232851],"genre_scores_gemma":[0.9697391,0.00005836857,0.02940855,0.00006719297,0.00008186425,0.00009302073,0.000003403578,0.000006812151,0.0005416639],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9513733,"threshold_uncertainty_score":0.4602412,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04806429966092279,"score_gpt":0.2965612503406855,"score_spread":0.2484969506797627,"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."}}