{"id":"W4417512795","doi":"10.36227/techrxiv.176617830.07292390/v1","title":"Channel-Informed RIS Analysis and Optimization Using Hybrid Ray-Tracing and Full-Wave Simulation Framework","year":2025,"lang":"","type":"preprint","venue":"","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; CMC Microsystems","keywords":"Process (computing); Channel (broadcasting); Coupling (piping); Finite element method; Electrical impedance; Matrix (chemical analysis); Transfer function; Transfer (computing)","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003386144,0.0008274493,0.001221181,0.002153832,0.0005304683,0.0003787552,0.0004285254,0.001014994,0.00009222662],"category_scores_gemma":[0.001045559,0.0009862933,0.0002251572,0.001938243,0.000246645,0.0007251919,0.001939586,0.001525287,0.000001319492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005207716,"about_ca_system_score_gemma":0.00009123678,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009548241,"about_ca_topic_score_gemma":0.00003990956,"domain_scores_codex":[0.9967958,0.00009469705,0.001332385,0.0009195814,0.0003153287,0.000542247],"domain_scores_gemma":[0.9956352,0.001490192,0.000628699,0.001770397,0.0003439078,0.00013168],"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":[0.00002876827,0.00001807915,0.000155959,0.0006067658,0.001221654,0.000001766741,0.000719519,0.9750155,0.00003740034,0.0002737635,0.000001196035,0.02191962],"study_design_scores_gemma":[0.0002824543,0.00002011051,0.000233572,0.0008483657,0.001101625,0.000003900842,0.001036921,0.9920072,0.001136171,0.002457157,0.00001917673,0.0008533548],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02270243,0.002711588,0.9718702,0.0001189014,0.0002823434,0.0008739437,0.00007397024,0.001077401,0.0002892561],"genre_scores_gemma":[0.5762547,0.01124275,0.4122242,0.0000192255,0.00002613131,0.00003568712,0.000125234,0.00003576199,0.00003639586],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.559646,"threshold_uncertainty_score":0.9992588,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03010319011212776,"score_gpt":0.2989252736493635,"score_spread":0.2688220835372357,"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."}}