{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001023979,0.0001117971,0.0001942855,0.00008672972,0.00002412792,0.0000145064,0.0001491475,0.00002515086,0.00002554388],"category_scores_gemma":[0.00006598356,0.000083478,0.0001652463,0.0001870823,0.00004824225,0.00005074069,0.00001633815,0.00005497002,0.000003054054],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007998048,"about_ca_system_score_gemma":0.00008070463,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005204275,"about_ca_topic_score_gemma":0.00002902013,"domain_scores_codex":[0.9990602,0.00005876283,0.0002952707,0.0001229466,0.0003097542,0.0001530251],"domain_scores_gemma":[0.9991682,0.0000438848,0.00007570977,0.0003199772,0.0003478421,0.00004441595],"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":[0.00003014822,0.00005666769,0.008211215,0.0001479521,0.0002034422,7.023684e-7,0.0003697475,0.1123521,0.7816985,0.00001965359,0.004053752,0.09285612],"study_design_scores_gemma":[0.0006408641,0.000004755289,0.001198161,0.00003217407,0.0001667254,0.00001684061,0.00008221968,0.7005156,0.296996,0.0001498333,0.0001117768,0.00008511719],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7103982,0.0003840835,0.2858478,0.0004247355,0.0002870957,0.0003358562,0.00004049326,0.0001046922,0.002177036],"genre_scores_gemma":[0.9838096,6.88245e-7,0.01603155,0.00002399031,0.0000312196,0.000008761137,0.00001132752,0.00002079093,0.00006207482],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5881634,"threshold_uncertainty_score":0.3404134,"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."}}