{"id":"W4213129316","doi":"10.1109/aps/ursi47566.2021.9704530","title":"A Metasurface for Biomedical Imaging Applications","year":2021,"lang":"en","type":"article","venue":"2021 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (APS/URSI)","topic":"Microwave Imaging and Scattering Analysis","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"International Laboratory for Brain, Music and Sound Research; University of Waterloo","funders":"Taif University","keywords":"Imaging phantom; Microwave imaging; Impression; Modality (human–computer interaction); Optics; Computer science; Microwave; Object (grammar); Energy (signal processing); Physics; Artificial intelligence; 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":[0.0008818314,0.0002250896,0.000244503,0.0002607271,0.000474596,0.0005053096,0.0002807719,0.0000512524,0.00004002511],"category_scores_gemma":[0.0001052427,0.0002175131,0.00009876882,0.0005364096,0.0003728463,0.00028013,0.00004677125,0.0001829609,0.00001269504],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001241421,"about_ca_system_score_gemma":0.00008744915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002290514,"about_ca_topic_score_gemma":0.00000671268,"domain_scores_codex":[0.9981117,0.00004132514,0.0003715583,0.0006145724,0.0004852027,0.0003756966],"domain_scores_gemma":[0.9990167,0.000121519,0.00009710116,0.0002283367,0.0003143002,0.0002220252],"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":[0.0000205481,0.00009641017,0.001104874,0.00009453837,0.0001181164,0.00001551297,0.0006027762,0.00280301,0.9593323,0.00131095,0.002018085,0.03248289],"study_design_scores_gemma":[0.0009912238,0.00006439738,0.0009054438,0.0004086635,0.0001477218,0.0002638842,0.0007842818,0.8128479,0.1239409,0.000390522,0.0585661,0.0006890327],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4907157,0.004545058,0.4259254,0.05345012,0.005624313,0.001369708,0.0003377472,0.0006871252,0.01734477],"genre_scores_gemma":[0.9921567,0.0006326254,0.005506005,0.0003783402,0.0003428699,0.00006611659,0.00007530116,0.00003082718,0.0008112542],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8353914,"threshold_uncertainty_score":0.8869928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01030349899560507,"score_gpt":0.256651547403038,"score_spread":0.246348048407433,"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."}}