{"id":"W1508202077","doi":"10.1109/iccw.2015.7247344","title":"3-Dimensional Large-Scale Channel Model for Urban Environments in mmWave Frequency","year":2015,"lang":"en","type":"article","venue":"","topic":"Millimeter-Wave Propagation and Modeling","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Fading; Path loss; Transmitter; Shadow mapping; Channel (broadcasting); Computer science; Delay spread; Ray tracing (physics); Log-distance path loss model; Standard deviation; Shadow (psychology); Topology (electrical circuits); Telecommunications; Mathematics; Statistics; Electrical engineering; Physics; Engineering; Optics; Wireless; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002053295,0.0005585859,0.0004546766,0.0004091181,0.0004257677,0.0007722696,0.0009112881,0.0008564509,0.001273427],"category_scores_gemma":[0.0005631182,0.0002733245,0.0007061906,0.001052858,0.0005022206,0.001163636,0.0004379231,0.0005149313,0.0004255357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007681439,"about_ca_system_score_gemma":0.0008190719,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01869272,"about_ca_topic_score_gemma":0.01587963,"domain_scores_codex":[0.9997601,0.00006138758,0.000009786501,0.00004358307,0.00007736361,0.0000478274],"domain_scores_gemma":[0.9996866,0.0001079392,0.00004796712,0.00003965117,0.00009703644,0.00002074262],"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":[0.000009889756,0.000008599501,0.0005879616,0.00001111267,0.000006353538,0.00004283388,0.00002013714,0.9935859,0.0009611332,0.002852307,0.0002558844,0.001657923],"study_design_scores_gemma":[0.000002270611,0.000005596718,0.0003079908,0.000001196463,0.000003205623,0.00002128394,0.00001285054,0.9982546,0.0001947893,0.0009484629,0.0002410107,0.00000672029],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1147395,0.000329988,0.8733978,0.0004343977,0.00009580894,0.00006320608,0.001340119,0.0008327677,0.008766458],"genre_scores_gemma":[0.9381686,0.0007466934,0.05412805,0.0001686284,0.00004462302,0.0001717062,0.0008262176,0.00009827758,0.005647287],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01869272,"threshold_uncertainty_score":0.03716785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04005453416138489,"score_gpt":0.2284579195814802,"score_spread":0.1884033854200953,"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."}}