{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002877575,0.0001835906,0.0002931051,0.00008006863,0.00004770495,0.00006438471,0.0003840563,0.00007484326,0.000118603],"category_scores_gemma":[0.00001611328,0.0001482511,0.0000835075,0.0001100434,0.0000356868,0.0001692039,0.0001129982,0.0001597501,0.00009627733],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001899291,"about_ca_system_score_gemma":0.0000168367,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003298529,"about_ca_topic_score_gemma":0.00003630084,"domain_scores_codex":[0.998794,0.00002637222,0.0003446313,0.0003911048,0.0001504819,0.0002934309],"domain_scores_gemma":[0.9988985,0.00009769652,0.00004447953,0.0007909214,0.00007156998,0.000096819],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006060933,0.0004127317,0.4076771,0.0004770744,0.00133202,0.00001543593,0.0002038023,0.002528254,0.01343207,0.00007704799,0.1348043,0.4384341],"study_design_scores_gemma":[0.02184929,0.001423912,0.1729407,0.0008197394,0.001189915,0.0001774496,0.000470464,0.6692771,0.01559099,0.0001170984,0.1121122,0.004031263],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7806227,0.00003876585,0.2157477,0.0001340862,0.0003180081,0.0003223029,0.0002775841,0.0003298957,0.002208924],"genre_scores_gemma":[0.9717134,0.000007481495,0.02696144,0.0001433856,0.0001487395,0.000003434594,0.0005576098,0.00005451247,0.0004100371],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6667488,"threshold_uncertainty_score":0.6045504,"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."}}