{"id":"W2980103410","doi":"10.1109/embc.2019.8856975","title":"Microwave Radar for Breast Screening: Initial Clinical Data with Suspicious-Lesion Patients","year":2019,"lang":"en","type":"article","venue":"","topic":"Microwave Imaging and Scattering Analysis","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Radar; Breast cancer; Lesion; SIGNAL (programming language); Computer science; Artificial intelligence; Medicine; Radiology; Medical physics; Pattern recognition (psychology); Computer vision; Cancer; Telecommunications; Pathology; Internal 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001713977,0.000475662,0.0005115272,0.000807027,0.0003008589,0.0003734719,0.0002567928,0.0005890774,0.001475297],"category_scores_gemma":[0.008292845,0.0001205608,0.00027349,0.0006107524,0.0004573684,0.0002809241,0.0003155759,0.0003496714,0.0007717704],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000179726,"about_ca_system_score_gemma":0.0001553746,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005220277,"about_ca_topic_score_gemma":0.0004107234,"domain_scores_codex":[0.9986821,0.0006298335,0.0001271879,0.0002339177,0.000239501,0.00008748154],"domain_scores_gemma":[0.9933338,0.004014282,0.0007009195,0.0006618224,0.0008867563,0.0004024931],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005650928,0.00158083,0.9136595,0.0001341198,0.0001869947,0.001530294,0.00082343,0.004677056,0.03626241,0.0001532653,0.001063989,0.0342772],"study_design_scores_gemma":[0.0001271364,0.007918131,0.9434039,0.00001216352,0.0001603624,0.006262001,0.0006687004,0.0121307,0.02722372,0.0001666203,0.00185263,0.00007388918],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974048,0.0001018281,0.001464803,0.00003325096,0.000004154366,0.00003181385,0.0004060949,0.00003698786,0.0005162624],"genre_scores_gemma":[0.9979991,0.00003939143,0.0008664582,0.00002870785,0.00001033797,0.00002368806,0.000840068,0.000009308073,0.0001829175],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001713977,"threshold_uncertainty_score":0.009064496,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03744740222307158,"score_gpt":0.2964485428061716,"score_spread":0.2590011405831,"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."}}