{"id":"W2577456775","doi":"","title":"Comparison of large scale parameters of mmWave wireless channel in 3 frequency bands","year":2016,"lang":"en","type":"article","venue":"International Symposium on Antennas and Propagation","topic":"Millimeter-Wave Propagation and Modeling","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Huawei Technologies (Canada)","funders":"","keywords":"Non-line-of-sight propagation; Extremely high frequency; Radio spectrum; Wireless; Channel (broadcasting); Electronic engineering; Computer science; Radio frequency; Telecommunications; Scale (ratio); Physics; 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":[0.0001996163,0.00011215,0.0001947001,0.0001666731,0.00001722171,0.00001040204,0.00009253969,0.00006549242,0.00002552212],"category_scores_gemma":[0.0000176975,0.00008624309,0.0000424145,0.00008606893,0.00003764116,0.0001378275,0.00001757896,0.00006907474,0.00000382804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004671873,"about_ca_system_score_gemma":0.000007473733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002227203,"about_ca_topic_score_gemma":0.0000419384,"domain_scores_codex":[0.9990438,0.00002648445,0.0004406295,0.0001535343,0.0002094769,0.0001261189],"domain_scores_gemma":[0.9995866,0.00005099443,0.0001127191,0.00009305577,0.0001194837,0.00003710064],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008039325,0.0001451023,0.01761147,0.00009303143,0.00004018758,0.000001117557,0.001311925,0.0009291315,0.9701866,0.001191278,0.00002140531,0.008388342],"study_design_scores_gemma":[0.001216229,0.0001835855,0.005088246,0.0005637833,0.000009973712,0.000003130195,0.0001854926,0.2978397,0.6935419,0.001142977,0.00003080919,0.0001941709],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9041004,0.00006095133,0.09359606,0.0003396223,0.0002809296,0.0001488555,0.0000440582,0.00002816532,0.001401005],"genre_scores_gemma":[0.9991372,0.0002145862,0.0005082634,0.00002898696,0.00002663042,0.00001533692,0.00001998023,0.00001459901,0.00003436511],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2969106,"threshold_uncertainty_score":0.3516891,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02022751335201344,"score_gpt":0.2677631562207183,"score_spread":0.2475356428687048,"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."}}