{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001887438,0.0004508035,0.0002616823,0.0003427666,0.0001386269,0.000553092,0.0006239149,0.001219236,0.002179276],"category_scores_gemma":[0.0003208132,0.000184216,0.0004129545,0.0003332775,0.0002737376,0.0005983601,0.000531422,0.0006524154,0.001171961],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002523164,"about_ca_system_score_gemma":0.0001860712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007417718,"about_ca_topic_score_gemma":0.0001097006,"domain_scores_codex":[0.9998288,0.00001978789,0.000007985126,0.0000282434,0.0001021975,0.00001302541],"domain_scores_gemma":[0.999867,0.00004048736,0.00002198029,0.00002968929,0.00002807887,0.00001272782],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003842356,0.0000151427,0.00008057946,0.0001570874,0.00001436778,0.0001594913,0.00002266677,0.0006611391,0.9576526,0.006257994,0.0005798217,0.03436065],"study_design_scores_gemma":[0.00003653168,0.0004902792,0.001031855,0.00009371011,0.00005994839,0.003575552,0.0000546565,0.04394285,0.8529606,0.009393372,0.08831878,0.00004185152],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09477384,0.03321314,0.8218343,0.002991064,0.001385903,0.0001591601,0.0003787026,0.002447659,0.04281632],"genre_scores_gemma":[0.5544106,0.00980366,0.4155553,0.001051363,0.0004373199,0.0001392065,0.0002861171,0.0001870766,0.01812931],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002179276,"threshold_uncertainty_score":0.007290363,"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."}}