{"id":"W2101899205","doi":"10.1109/tcomm.2005.849792","title":"Accurate Performance Evaluation of Time-Hopping and Direct-Sequence UWB Systems in Multi-User Interference","year":2005,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Ultra-Wideband Communications Technology","field":"Engineering","cited_by":128,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Time-hopping; Keying; Additive white Gaussian noise; Interference (communication); Bit error rate; Algorithm; Frequency-hopping spread spectrum; Phase-shift keying; Gaussian noise; Computer science; Modulation (music); Electronic engineering; Gaussian; Spread spectrum; Noise (video); Signal-to-noise ratio (imaging); Binary number; Telecommunications; White noise; Mathematics; Decoding methods; Physics; Engineering; Acoustics; Artificial intelligence; Pulse-amplitude modulation; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002402515,0.0006415145,0.001171868,0.0008897747,0.0003771134,0.0009832334,0.0008139248,0.001092791,0.0007114608],"category_scores_gemma":[0.01169511,0.0003207695,0.0004052138,0.0008251919,0.0007250831,0.001555726,0.0009447698,0.000460105,0.0003254625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001199928,"about_ca_system_score_gemma":0.0006262966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00168306,"about_ca_topic_score_gemma":0.0009498363,"domain_scores_codex":[0.9972531,0.0007181748,0.0001086579,0.000175792,0.001534682,0.0002096088],"domain_scores_gemma":[0.9947753,0.003411242,0.000294603,0.0006322033,0.0008275381,0.00005914388],"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":[0.0003015382,0.0000327686,0.002158525,0.0001309559,0.0000604771,0.0001982646,0.0001646591,0.9163761,0.01502129,0.0122437,0.0002082048,0.05310351],"study_design_scores_gemma":[0.000006561263,0.00009686034,0.0005699719,0.00001019688,0.00001307212,0.000168616,0.00001601657,0.9886671,0.00883253,0.00143909,0.0001645347,0.00001533518],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1819588,0.001626472,0.8113549,0.0001018787,0.00003699539,0.00004097231,0.00006739061,0.0007890795,0.004023504],"genre_scores_gemma":[0.9643386,0.0003858737,0.03447491,0.00002983042,0.00001567238,0.00002861457,0.00004678653,0.00002756181,0.0006521457],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002402515,"threshold_uncertainty_score":0.01270586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07523173087991988,"score_gpt":0.3045697179082266,"score_spread":0.2293379870283067,"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."}}