{"id":"W2043610199","doi":"10.1002/wcm.186","title":"ZCZ‐CDMA and OFDMA using M‐QAM for broadband wireless communications","year":2004,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Multipath propagation; Code division multiple access; Fading; Orthogonal frequency-division multiple access; Wireless; Wireless broadband; Computer network; Electronic engineering; Orthogonal frequency-division multiplexing; Telecommunications; Channel (broadcasting); Wireless network; 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":[0.0006315858,0.0003963445,0.0003368666,0.0005600735,0.0003832644,0.001004163,0.0003277383,0.0006283356,0.001024864],"category_scores_gemma":[0.001432199,0.0001923964,0.0002664705,0.0005832298,0.000583712,0.0007610488,0.0005050963,0.0003340903,0.0003486471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004954332,"about_ca_system_score_gemma":0.0006664508,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00124314,"about_ca_topic_score_gemma":0.001212524,"domain_scores_codex":[0.999586,0.0001706614,0.00001536149,0.00004757208,0.0001210686,0.00005926796],"domain_scores_gemma":[0.9992529,0.0004115124,0.000111496,0.00007712213,0.0001188848,0.00002810917],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008308021,0.0001749509,0.007472975,0.000346673,0.0001433138,0.0005577689,0.0001613081,0.3340394,0.09786803,0.2221981,0.002107876,0.3340988],"study_design_scores_gemma":[0.00008565063,0.0006047094,0.002195889,0.00007219415,0.0001276074,0.001001946,0.0001179226,0.9067898,0.04084536,0.02856789,0.01954022,0.00005076704],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.4781636,0.01069293,0.474194,0.0007038856,0.0002264591,0.0001773769,0.00008986034,0.0003753877,0.03537646],"genre_scores_gemma":[0.9030676,0.003628305,0.08735779,0.0001383846,0.0001369878,0.00006908999,0.00005987794,0.00001636499,0.005525553],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.00124314,"threshold_uncertainty_score":0.003594637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05897994334119107,"score_gpt":0.3431216849068068,"score_spread":0.2841417415656158,"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."}}