{"id":"W4387573743","doi":"10.1049/mia2.12412","title":"Generalisable convolutional neural network model for radio wave propagation in tunnels","year":2023,"lang":"en","type":"article","venue":"IET Microwaves Antennas & Propagation","topic":"Millimeter-Wave Propagation and Modeling","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"CHIST-ERA; Irish Research eLibrary","keywords":"Radio propagation; Extrapolation; Interpolation (computer graphics); Computer science; Radio propagation model; Convolutional neural network; Fidelity; Artificial neural network; Signal strength; Backpropagation; Electronic engineering; Wireless; Scale (ratio); Representation (politics); Simulation; Algorithm; Artificial intelligence; Engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006387426,0.0003219904,0.0003101961,0.0002910545,0.0001902923,0.0001062645,0.0001461833,0.0001771973,0.00001791899],"category_scores_gemma":[0.00005364,0.0003363182,0.0001410484,0.0006279375,0.00005438933,0.0004811145,0.00004390808,0.0002269537,0.00004943797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002024548,"about_ca_system_score_gemma":0.00006903574,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001150003,"about_ca_topic_score_gemma":0.00005066734,"domain_scores_codex":[0.9978408,0.00005973206,0.0006842149,0.0004522229,0.0002529924,0.0007101048],"domain_scores_gemma":[0.9992802,0.00005911381,0.0001104881,0.0002411827,0.0002063165,0.0001026662],"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":[0.00003874062,0.0000213219,0.00007970235,0.0001176097,0.00002103462,0.000003084792,0.0004367284,0.6850974,0.3101799,0.0004148124,0.002014359,0.001575238],"study_design_scores_gemma":[0.0008512294,0.00005126162,0.000379742,0.00009079699,0.00002097712,0.00001462652,0.00005943682,0.9665892,0.02790315,0.003405083,0.0002464159,0.0003881099],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2907138,0.000327595,0.7061988,0.0003220988,0.0005329076,0.001190008,0.00005208352,0.000540779,0.0001219681],"genre_scores_gemma":[0.9866372,0.0002117058,0.0104904,0.0001576844,0.0004439684,0.0003106706,0.0008736144,0.000102079,0.000772687],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6959234,"threshold_uncertainty_score":0.9999089,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04702343883669312,"score_gpt":0.2429297839117201,"score_spread":0.195906345075027,"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."}}