{"id":"W2137493711","doi":"10.1109/8.855493","title":"A hybrid technique based on combining ray tracing and FDTD methods for site-specific modeling of indoor radio wave propagation","year":2000,"lang":"en","type":"article","venue":"IEEE Transactions on Antennas and Propagation","topic":"Millimeter-Wave Propagation and Modeling","field":"Engineering","cited_by":170,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Finite-difference time-domain method; Ray tracing (physics); Robustness (evolution); Computer science; Classification of discontinuities; Rayleigh distribution; Finite difference method; Acoustics; Radio propagation; Wave propagation; Radio wave; Rayleigh scattering; Optics; Physics; Telecommunications; Mathematics; Mathematical analysis","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":[0.0003053213,0.0004669578,0.0004414309,0.0006568953,0.0002567914,0.0004443033,0.0006724022,0.0006261201,0.001078562],"category_scores_gemma":[0.0005836767,0.0003316831,0.0006440627,0.0006642008,0.0002855536,0.0007376675,0.0005354556,0.0005358944,0.0004774525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002349332,"about_ca_system_score_gemma":0.0004011333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008968649,"about_ca_topic_score_gemma":0.001261152,"domain_scores_codex":[0.999786,0.00003580273,0.0000111173,0.00002942486,0.0001229069,0.00001489646],"domain_scores_gemma":[0.9997019,0.0001338501,0.00002867175,0.00006253313,0.00006297306,0.00001002994],"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":[0.00008318019,0.000103574,0.001889502,0.0003897075,0.000151851,0.0002916037,0.0003757834,0.3179562,0.1916206,0.02701134,0.002247679,0.4578789],"study_design_scores_gemma":[0.00001430279,0.00008634327,0.0003499207,0.00001939365,0.00003355277,0.0005598497,0.00003133914,0.9555034,0.02783107,0.002897088,0.01263889,0.00003494934],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003159131,0.0000555699,0.9958525,0.00001471049,0.00001686351,0.00001325603,0.00001053449,0.0003771315,0.000500335],"genre_scores_gemma":[0.1022078,0.0002303633,0.8956045,0.00003119793,0.00002021568,0.00008219891,0.00006380161,0.00008273085,0.001677089],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001078562,"threshold_uncertainty_score":0.003608167,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03095242872558658,"score_gpt":0.2601042083395884,"score_spread":0.2291517796140018,"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."}}