{"id":"W1944263649","doi":"10.1109/usnc-ursi.2015.7303591","title":"Detailed evaluation of artifact removal algorithms for radar-based microwave imaging of the breast","year":2015,"lang":"en","type":"article","venue":"","topic":"Microwave Imaging and Scattering Analysis","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Artifact (error); Radar; Computer science; Microwave imaging; Stage (stratigraphy); Breast cancer; Radar imaging; Antenna (radio); Computer vision; Breast imaging; Identification (biology); Microwave; Artificial intelligence; Mammography; Cancer; Medicine; Telecommunications; Geology","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":[0.003830838,0.001136242,0.0007023853,0.001415584,0.0004416323,0.001452298,0.0008754256,0.000931269,0.002446584],"category_scores_gemma":[0.01354253,0.0002780617,0.0007741864,0.001137177,0.0002426216,0.001207836,0.0004978976,0.0005716823,0.001126643],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005036235,"about_ca_system_score_gemma":0.0009318682,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002304215,"about_ca_topic_score_gemma":0.002988484,"domain_scores_codex":[0.997995,0.0004584747,0.0002370089,0.0001624847,0.001028474,0.0001185028],"domain_scores_gemma":[0.9925147,0.003321169,0.0003690122,0.0006303228,0.003077835,0.00008702723],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00107923,0.0002643514,0.00316393,0.0005894189,0.000280036,0.0001920653,0.0001532958,0.1082572,0.1085566,0.003386806,0.002459742,0.7716174],"study_design_scores_gemma":[0.00007665545,0.0006599324,0.007378484,0.00009620397,0.0001504686,0.0009956342,0.0001277671,0.8372205,0.1398127,0.002104811,0.01129544,0.00008131815],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04685953,0.00195773,0.9470896,0.0001167872,0.00009468473,0.0002117136,0.0001669958,0.00183282,0.001670265],"genre_scores_gemma":[0.1158418,0.001465281,0.8787988,0.00007953,0.00003820949,0.0001119155,0.001014965,0.0004617359,0.00218763],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003830838,"threshold_uncertainty_score":0.02025962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0366023496742985,"score_gpt":0.2652836236261514,"score_spread":0.2286812739518529,"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."}}