{"id":"W2019459905","doi":"10.1109/aps.2014.6904406","title":"SNR assessment of microwave imaging systems","year":2014,"lang":"en","type":"article","venue":"","topic":"Microwave Imaging and Scattering Analysis","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Microwave imaging; Calibration; Computer science; Microwave; Signal-to-noise ratio (imaging); Noise (video); Data acquisition; Computer vision; Electronic engineering; Artificial intelligence; Engineering; Telecommunications; Physics; Image (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":[],"consensus_categories":[],"category_scores_codex":[0.0002352227,0.0001013994,0.000196062,0.0001034375,0.00002075616,0.0000390092,0.0001076651,0.00001792011,0.00003642752],"category_scores_gemma":[0.000005821903,0.00009380165,0.00006797825,0.0001027442,0.00002086766,0.00004414179,0.0000182311,0.00007250447,0.00002069974],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000311683,"about_ca_system_score_gemma":0.000005065713,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008689542,"about_ca_topic_score_gemma":0.0000031067,"domain_scores_codex":[0.9993786,0.0000250095,0.0002227388,0.0001122811,0.00009881477,0.000162618],"domain_scores_gemma":[0.9996129,0.00003191821,0.00002718237,0.0002544618,0.00003073996,0.00004275814],"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":[6.105191e-7,0.00002269855,0.02538571,0.0003884592,0.0001638403,0.000002566001,0.0001249678,0.08504742,0.8608598,0.002156206,0.01243927,0.01340848],"study_design_scores_gemma":[0.0001162709,0.000004367914,0.00221379,0.00004399875,0.00003043574,0.00001007967,0.00006787034,0.9769304,0.0156097,0.0000321136,0.004791965,0.0001490309],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0921884,0.0002508489,0.7987251,0.00007768229,0.0003254169,0.00004708492,0.000002562007,0.000306001,0.1080769],"genre_scores_gemma":[0.994966,0.00001003947,0.004534089,0.0000266806,0.00005115196,0.000003348589,0.00000431124,0.0000202296,0.0003841116],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9027777,"threshold_uncertainty_score":0.382512,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004271977153980182,"score_gpt":0.212371107245028,"score_spread":0.2080991300910479,"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."}}