{"id":"W3131641899","doi":"10.1109/ieeeconf35879.2020.9329920","title":"Ray-Tracing Simulations of mm-Wave Channels with FDTD-based Diffuse Scattering Models","year":2020,"lang":"en","type":"article","venue":"","topic":"Millimeter-Wave Propagation and Modeling","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Alexander S. Onassis Public Benefit Foundation","keywords":"Finite-difference time-domain method; Ray tracing (physics); Scattering; Computer science; Channel (broadcasting); Wireless; Distributed ray tracing; Electronic engineering; Optics; Algorithm; Physics; Telecommunications; 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":[0.00004714598,0.0001528356,0.00018974,0.00008721375,0.00004437581,0.00002879101,0.00006801736,0.00004459615,0.0001021368],"category_scores_gemma":[0.000009846764,0.0001370747,0.00004902138,0.0001775729,0.00001778479,0.0001885854,0.00001833648,0.0001046808,0.000007338599],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002000874,"about_ca_system_score_gemma":0.00001463606,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008971966,"about_ca_topic_score_gemma":0.000005172115,"domain_scores_codex":[0.9992083,0.00001208953,0.0002664955,0.0001696804,0.0001564352,0.000186961],"domain_scores_gemma":[0.9995868,0.00004157073,0.00003527666,0.0001552077,0.00006326436,0.0001179225],"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":[0.000009314824,0.0000131959,0.00001294476,0.0001053154,0.00002192054,0.000001479001,0.0007085214,0.9235587,0.07510536,0.00002417013,0.000016564,0.0004225298],"study_design_scores_gemma":[0.0005100514,0.00003097791,0.000004010607,0.00005025742,0.00001605636,6.290837e-7,0.00007472688,0.8560934,0.1430058,0.00005077216,0.00001050185,0.0001527877],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3273628,0.00002323672,0.6712883,0.0001279331,0.00004028198,0.0001251076,0.00000779482,0.0002133871,0.0008111801],"genre_scores_gemma":[0.9824834,0.00000432792,0.01707758,0.0002922537,0.00005203973,0.000008195928,0.00001530275,0.00004514543,0.00002173968],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6551206,"threshold_uncertainty_score":0.5589743,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05455042560794445,"score_gpt":0.2177004027689571,"score_spread":0.1631499771610127,"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."}}