{"id":"W4411086864","doi":"10.1109/lwc.2025.3577135","title":"Prediction of Wireless Channel Statistics With Ray Tracing and Uncalibrated Digital Twin","year":2025,"lang":"en","type":"article","venue":"IEEE Wireless Communications Letters","topic":"Advanced Optical Sensing Technologies","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Ray tracing (physics); Wireless; Channel (broadcasting); Shadow mapping; Statistics; Algorithm; Artificial intelligence; Computer network; Telecommunications; Mathematics","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":[0.001166991,0.001062071,0.0008982932,0.0009802955,0.0003767648,0.001226988,0.001543485,0.0009319636,0.0009196768],"category_scores_gemma":[0.007517451,0.0007053474,0.0005979224,0.001200916,0.001464929,0.002320907,0.001720319,0.001749427,0.0003117598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009944864,"about_ca_system_score_gemma":0.001464263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007025088,"about_ca_topic_score_gemma":0.005447208,"domain_scores_codex":[0.9992719,0.000144105,0.00003591849,0.0001427497,0.0003132972,0.00009200263],"domain_scores_gemma":[0.997494,0.001237073,0.0004044825,0.0003771114,0.000369257,0.0001180569],"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":[0.00007083311,0.00002494252,0.001525303,0.00002060371,0.00001604966,0.00006024103,0.00004122315,0.9680024,0.002139706,0.01281415,0.0002966468,0.01498804],"study_design_scores_gemma":[0.000001703326,0.000006700813,0.00008322823,0.000001486187,0.000001408261,0.00001084886,0.00000216619,0.9972571,0.0005508261,0.001979294,0.0001006726,0.000004565171],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0141396,0.00006067932,0.9848533,0.00005546697,0.00001882107,0.00001226385,0.00006129104,0.0003466382,0.0004519885],"genre_scores_gemma":[0.7459009,0.0003988029,0.2507147,0.00009791916,0.00007233553,0.0000838012,0.0005276993,0.0001985222,0.002005288],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007025088,"threshold_uncertainty_score":0.01396841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01635801282410806,"score_gpt":0.2388937724619981,"score_spread":0.2225357596378901,"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."}}