{"id":"W2171744213","doi":"10.1109/twc.2006.04530","title":"Modeling of multiple access interference and BER derivation for TH and DS UWB multiple access systems","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Ultra-Wideband Communications Technology","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Additive white Gaussian noise; Bit error rate; Fading; Algorithm; Ultra-wideband; Pulse-position modulation; Computer science; Time-hopping; Modulation (music); Nakagami distribution; Interference (communication); Mathematics; Channel (broadcasting); Pulse-amplitude modulation; Telecommunications; Decoding methods; Pulse (music); Physics","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":[0.0001315797,0.000204292,0.0002822547,0.0003151329,0.0004047958,0.0001277277,0.001160924,0.0001723814,0.000002247901],"category_scores_gemma":[0.00001849238,0.0002264075,0.00005577073,0.0003498482,0.0002112648,0.000530003,0.00003163181,0.0003280317,9.281966e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006404414,"about_ca_system_score_gemma":0.00002236068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001139282,"about_ca_topic_score_gemma":0.003272896,"domain_scores_codex":[0.9989135,0.00006576959,0.0005158469,0.0002100915,0.0000915835,0.0002032324],"domain_scores_gemma":[0.9973558,0.0008373408,0.00008630347,0.001496143,0.0001790986,0.0000452729],"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":[0.00003998895,0.0003706613,0.001719268,0.0002891565,0.0001394367,1.015235e-7,0.0004271285,0.9537451,0.01963841,0.002944615,0.00005064548,0.02063554],"study_design_scores_gemma":[0.0005971164,0.00002940693,0.0004423256,0.0001373201,0.00005481563,0.000005724202,0.0001817183,0.9858577,0.0119349,0.0003699142,0.0001702704,0.0002188173],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.305388,0.0006532831,0.6926273,0.0002103071,0.00008166065,0.0005139666,0.0001024085,0.0002720089,0.0001510194],"genre_scores_gemma":[0.9919346,0.001911919,0.005171034,0.00001195689,0.000008773426,0.0008445038,0.00004943624,0.00004663687,0.00002111395],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6874563,"threshold_uncertainty_score":0.9232631,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04244264657749041,"score_gpt":0.2760460784515616,"score_spread":0.2336034318740712,"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."}}