{"id":"W3205827821","doi":"10.23919/ursigass51995.2021.9560554","title":"Strategies for Synergistic Use of Microwave and Ultrasound Data For Biomedical Imaging","year":2021,"lang":"en","type":"article","venue":"","topic":"Microwave Imaging and Scattering Analysis","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Microwave imaging; Ultrasound; Regularization (linguistics); Microwave; Computer science; Ultrasound imaging; Artificial intelligence; Biomedical engineering; Computer vision; Medical physics; Acoustics; Medicine; Physics; Telecommunications","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":[0.0001232446,0.0001005587,0.0001889743,0.00006001054,0.00003575119,0.0001362757,0.0001142898,0.00002599443,0.000016208],"category_scores_gemma":[0.0001559378,0.00009677009,0.0000458723,0.00008888918,0.0000728013,0.0001722591,0.00004576307,0.00004017786,5.624323e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009233589,"about_ca_system_score_gemma":0.00003231516,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004116123,"about_ca_topic_score_gemma":0.00003774968,"domain_scores_codex":[0.9993435,0.000008163804,0.0002008245,0.0002188217,0.00005510147,0.0001736212],"domain_scores_gemma":[0.9990525,0.0004333433,0.00001945022,0.0003844553,0.00006055,0.00004969019],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004524244,0.00001907042,0.0002434192,0.0004885865,0.0001729093,0.00000409497,0.00008894932,0.0005262266,0.9637941,0.0007861101,0.02979328,0.004078733],"study_design_scores_gemma":[0.0008237917,0.0000213597,0.0002423691,0.0001373087,0.0004392052,0.00009225524,0.001709853,0.8409512,0.1008964,0.001987778,0.05220237,0.0004961538],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04677138,0.000615717,0.951587,0.0001698826,0.0001028559,0.00006931039,0.0004430135,0.0000784932,0.0001623971],"genre_scores_gemma":[0.92451,0.00006226703,0.07460167,0.00004807241,0.0000511264,0.000007365476,0.0005281069,0.00002321645,0.0001681952],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8777386,"threshold_uncertainty_score":0.394617,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03716998802294701,"score_gpt":0.2646025815230232,"score_spread":0.2274325935000762,"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."}}