{"id":"W4245216946","doi":"10.1109/iembs.2006.4398395","title":"Hybrid Microwave Tomography Technique for Breast Cancer Imaging","year":2006,"lang":"en","type":"article","venue":"Conference proceedings","topic":"Microwave Imaging and Scattering Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Microwave imaging; Inverse scattering problem; Dielectric; Inverse problem; Permittivity; Tomography; Mammography; Microwave; Computer science; Image resolution; Breast cancer; Resolution (logic); Materials science; Optics; Scattering; Physics; Artificial intelligence; Cancer; Mathematics; Telecommunications; Mathematical analysis; Optoelectronics; Medicine","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000128228,0.0002383528,0.0002313206,0.0002350768,0.00009846225,0.0002096642,0.0002254914,0.00003911361,0.00005806131],"category_scores_gemma":[0.000004315598,0.0002488908,0.0001414014,0.0002087536,0.00006975966,0.0001932321,0.00002526151,0.0001469668,0.0000075089],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006090481,"about_ca_system_score_gemma":0.00002027763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001115242,"about_ca_topic_score_gemma":0.000006449437,"domain_scores_codex":[0.9989341,0.000001980186,0.0002412126,0.0003048235,0.0001004694,0.0004173411],"domain_scores_gemma":[0.9995234,0.00001139034,0.00004956179,0.0001036023,0.0002468196,0.00006520645],"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":[0.000005628964,0.00001330267,0.01149714,0.0002189616,0.00003700914,0.000001544737,0.00008291269,0.00004900288,0.9561991,0.0003783273,0.02241815,0.009098923],"study_design_scores_gemma":[0.0004219293,0.00001060746,0.006139339,0.0003653161,0.000142548,0.000191215,0.0001268123,0.04671878,0.9300284,0.006291258,0.008665725,0.0008980213],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3454644,0.00153,0.6333199,0.00268692,0.0003720788,0.000983074,0.0003499818,0.002153538,0.01314013],"genre_scores_gemma":[0.9948839,0.00003873572,0.004208688,0.00008773392,0.0002009544,0.0003249839,0.00001445623,0.00005236797,0.0001881985],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6494194,"threshold_uncertainty_score":0.9999963,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00628418022548791,"score_gpt":0.2077880446196953,"score_spread":0.2015038643942074,"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."}}