{"id":"W4238196375","doi":"10.36227/techrxiv.11833095.v1","title":"On Microwave Breast Imaging with Ultrasound Spatial Priors","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Microwave Imaging and Scattering Analysis","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Prior probability; Ultrasound; Microwave imaging; Microwave; Ultrasound imaging; Computer science; Breast ultrasound; Breast imaging; Artificial intelligence; Computer vision; Mammography; Physics; Medicine; Acoustics; Bayesian probability; Telecommunications; Breast cancer; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006810877,0.0006783081,0.0003426921,0.0004217182,0.0001451876,0.0006461697,0.0004679175,0.0008254836,0.00161719],"category_scores_gemma":[0.003533714,0.0004282135,0.0003284358,0.0004176833,0.001284771,0.00105647,0.001002934,0.0008681212,0.0005628524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002910102,"about_ca_system_score_gemma":0.0002184648,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007320954,"about_ca_topic_score_gemma":0.000721015,"domain_scores_codex":[0.9996978,0.0001330779,0.000008178947,0.00004297145,0.0001007062,0.00001724971],"domain_scores_gemma":[0.9985192,0.001140165,0.0001000731,0.0001166822,0.0001000256,0.0000237771],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002644051,0.00008738692,0.0007628655,0.0005002853,0.00006031764,0.0004564643,0.0002437791,0.4929054,0.07145993,0.2488558,0.003013722,0.1813897],"study_design_scores_gemma":[0.00001806624,0.00009954799,0.000707394,0.00006960361,0.00002055425,0.0004004151,0.00003320424,0.8872867,0.02466722,0.07860655,0.008050682,0.00004008164],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008803438,0.000696988,0.9862399,0.0003545188,0.00002569023,0.00001616232,0.00003916135,0.00007260391,0.003751546],"genre_scores_gemma":[0.2939342,0.007150046,0.6859673,0.0005760623,0.0004787994,0.0001241839,0.0002407227,0.0002542532,0.0112744],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00161719,"threshold_uncertainty_score":0.005410075,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00572864027816369,"score_gpt":0.1922873104122928,"score_spread":0.1865586701341291,"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."}}