{"id":"W2167988080","doi":"10.2528/pier11050408","title":"A BIMODAL RECONSTRUCTION METHOD FOR BREAST CANCER IMAGING","year":2011,"lang":"en","type":"article","venue":"Electromagnetic waves","topic":"Microwave Imaging and Scattering Analysis","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; CancerCare Manitoba","funders":"","keywords":"Electrical impedance tomography; Breast cancer; Microwave imaging; Breast imaging; Modality (human–computer interaction); Microwave; Iterative reconstruction; Radar; Artificial intelligence; Computer science; Computer vision; Tomography; Medical physics; Mammography; Medicine; Radiology; Cancer; 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":[0.0006667077,0.0003375233,0.0003488119,0.0006068881,0.0001577815,0.0003754644,0.0004843103,0.0004625555,0.002117242],"category_scores_gemma":[0.001481028,0.0001962653,0.0003433018,0.0004195993,0.000251383,0.0004172534,0.0005343347,0.0004929942,0.0007924036],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002061194,"about_ca_system_score_gemma":0.0003761976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005486076,"about_ca_topic_score_gemma":0.0008180907,"domain_scores_codex":[0.9997602,0.0000648104,0.00001132651,0.00005128274,0.00009296872,0.00001945987],"domain_scores_gemma":[0.9997062,0.0001063538,0.00003049257,0.00004097209,0.00009645753,0.000019504],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003148934,0.00005765936,0.001208525,0.0001667182,0.00004665427,0.0001276114,0.0000982015,0.06510618,0.1763869,0.01273053,0.001490529,0.7422656],"study_design_scores_gemma":[0.00002507881,0.0001083173,0.001204568,0.00001118105,0.00002752226,0.0006845095,0.00002818619,0.9436302,0.04461726,0.003238832,0.006388045,0.00003643142],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004727321,0.0001283217,0.994534,0.00003882783,0.00001098803,0.00001260077,0.00001829049,0.0002034151,0.0003262279],"genre_scores_gemma":[0.141156,0.0003059983,0.8551892,0.00007206552,0.00003388296,0.00006994122,0.0001395196,0.00009203302,0.002941375],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002117242,"threshold_uncertainty_score":0.00708288,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008299625549835632,"score_gpt":0.223366087211985,"score_spread":0.2150664616621493,"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."}}