{"id":"W4417131937","doi":"10.1109/ap-s/cnc-usnc-ursi55537.2025.11266116","title":"Synthesis of an Open Building Dataset Enabling Accurate Millimetre-Wave Propagation Simulation","year":2025,"lang":"","type":"article","venue":"","topic":"Millimeter-Wave Propagation and Modeling","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Communications Research Centre Canada","funders":"","keywords":"Path (computing); Path loss; Propagation of uncertainty; Open source; Lidar","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":[0.0008133228,0.001104667,0.0006510755,0.001985445,0.0004497574,0.001135643,0.00202454,0.0008127015,0.003699967],"category_scores_gemma":[0.002821046,0.0004936485,0.001104258,0.002103152,0.0003918942,0.001005576,0.00147422,0.001127713,0.002848375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006727381,"about_ca_system_score_gemma":0.00132145,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01482332,"about_ca_topic_score_gemma":0.02843951,"domain_scores_codex":[0.9992773,0.0001045184,0.00005817796,0.0001295978,0.0003270347,0.0001035008],"domain_scores_gemma":[0.998863,0.0002303607,0.00006903326,0.0003087042,0.0004508053,0.00007808458],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003338121,0.0006641439,0.01497436,0.0008697414,0.0002165245,0.0005626836,0.0002849925,0.7379702,0.0125917,0.01229765,0.09566172,0.1235725],"study_design_scores_gemma":[0.0001368793,0.0001359595,0.01173418,0.000147284,0.00004638073,0.0001907551,0.0003676381,0.8760176,0.01957856,0.007148264,0.08438119,0.0001153862],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"dataset","genre_scores_codex":[0.1659532,0.0004609707,0.4665965,0.0006572514,0.0007311811,0.0008081828,0.3188341,0.02850151,0.01745703],"genre_scores_gemma":[0.2253384,0.0003629652,0.2341853,0.0001254404,0.00005661213,0.0009771676,0.5354213,0.001183606,0.002349228],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.01482332,"threshold_uncertainty_score":0.02947408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06094583877738417,"score_gpt":0.3255075588510793,"score_spread":0.2645617200736951,"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."}}