{"id":"W4410583230","doi":"10.23919/eucap63536.2025.10999434","title":"A Diffusion-Based Propagation Model for Path Loss Prediction in Indoor Environments","year":2025,"lang":"en","type":"article","venue":"","topic":"Millimeter-Wave Propagation and Modeling","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Diffusion; Path loss; Log-distance path loss model; Path (computing); Computer network; Physics; Telecommunications; Wireless","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":[0.0001101175,0.00009177433,0.00008589004,0.0001435574,0.00003494912,0.00001359952,0.00004614157,0.00006672599,0.00001634286],"category_scores_gemma":[0.0000155214,0.00008802977,0.000032097,0.00008553217,0.000007682304,0.00007361129,0.00001038615,0.00006482494,0.000007093515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001090779,"about_ca_system_score_gemma":0.00001963008,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003835222,"about_ca_topic_score_gemma":0.000009814376,"domain_scores_codex":[0.9994175,0.000008706101,0.0002181503,0.0001408564,0.000084332,0.0001304454],"domain_scores_gemma":[0.9998237,0.00001974057,0.00001493661,0.0001056909,0.00001053741,0.00002533619],"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":[0.00002860222,0.00005420483,0.001334427,0.00009592806,0.000007805026,2.379899e-7,0.0001052606,0.9425333,0.04840197,0.0001163285,0.0001593487,0.007162577],"study_design_scores_gemma":[0.0008494185,0.00001570426,0.000356581,0.00004335703,0.000007076198,7.853014e-8,0.00001241376,0.9747722,0.02303782,0.0007534419,0.00007638634,0.00007557884],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.193504,0.0000189155,0.8050193,0.0000476827,0.00007861191,0.0004530982,0.00001344938,0.00009520465,0.0007696986],"genre_scores_gemma":[0.9914225,0.00001248767,0.007272629,0.0001307516,0.00001128216,0.000231999,0.00005778022,0.00001408931,0.0008465122],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7979184,"threshold_uncertainty_score":0.358975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0117638737241766,"score_gpt":0.2140991369705316,"score_spread":0.202335263246355,"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."}}