{"id":"W2972698991","doi":"","title":"A Combined Algorithm for High Resolution Microwave Breast Imaging Using Eigenfunction-based Prior","year":2019,"lang":"en","type":"article","venue":"European Conference on Antennas and Propagation","topic":"Microwave Imaging and Scattering Analysis","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Eigenfunction; Microwave imaging; Algorithm; Finite element method; Contrast (vision); Inversion (geology); Computer science; High contrast; Microwave; Iterative method; Mathematics; Physics; Computer vision; Optics; Eigenvalues and eigenvectors; 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":[0.0002944559,0.0001800577,0.0001672786,0.0001457192,0.0001313831,0.0001602826,0.00007457349,0.0000236258,0.00003467236],"category_scores_gemma":[0.000008267923,0.0001740936,0.00005337159,0.0001153059,0.00003512954,0.0001085488,0.00001396977,0.0001135872,0.00004678691],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005119697,"about_ca_system_score_gemma":0.00002228327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002627774,"about_ca_topic_score_gemma":0.000001910199,"domain_scores_codex":[0.9991073,0.00007461868,0.0002204593,0.0002819351,0.0001001281,0.0002155745],"domain_scores_gemma":[0.9995406,0.00002245071,0.00006682047,0.0001877215,0.0001250381,0.00005732698],"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":[0.00009136272,0.00004791076,0.001260369,0.0001890452,0.00006636135,0.000007824126,0.0002102198,0.003717912,0.6350651,0.0005248984,0.0002292712,0.3585897],"study_design_scores_gemma":[0.0007533604,0.00006236966,0.003592989,0.0001945057,0.00003590645,0.00001206601,0.0000616551,0.989871,0.005010628,0.0000528797,0.0001197716,0.0002328802],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2850243,0.00005618032,0.7126976,0.0002511515,0.0002988735,0.0003314691,0.00003825459,0.000219868,0.001082332],"genre_scores_gemma":[0.992038,0.00001409417,0.007410529,0.0001189298,0.00007979138,0.000005170961,0.00009704006,0.00004553869,0.0001909551],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9861531,"threshold_uncertainty_score":0.7099332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0144179078259458,"score_gpt":0.2106602302264961,"score_spread":0.1962423224005503,"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."}}