{"id":"W2997748230","doi":"","title":"Challenges with Machine Learning for Microwave Breast Tumor detection","year":2019,"lang":"en","type":"article","venue":"Journal of Computational Vision and Imaging Systems","topic":"Microwave Imaging and Scattering Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Breast tumor; Microwave; Microwave imaging; Artificial intelligence; Breast tissue; Modality (human–computer interaction); Breast cancer; Computer science; Breast MRI; Machine learning; Mammography; Medical physics; Medicine; Telecommunications; Internal medicine; Cancer","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01176599,0.001060611,0.001820955,0.001776923,0.0008513505,0.003951883,0.002861935,0.003410827,0.002719024],"category_scores_gemma":[0.02988317,0.0006564542,0.0009612719,0.001921445,0.001904137,0.005198215,0.002120225,0.004742492,0.002704944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001310918,"about_ca_system_score_gemma":0.001295648,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002737973,"about_ca_topic_score_gemma":0.001965398,"domain_scores_codex":[0.9932326,0.003440616,0.0003898229,0.000962779,0.001804255,0.0001700103],"domain_scores_gemma":[0.9626644,0.03061532,0.0007521948,0.001956795,0.003684897,0.0003262746],"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":[0.000184144,0.0003262846,0.004688344,0.001268292,0.0002988937,0.0001939963,0.0003293903,0.1405841,0.002514672,0.06893674,0.02638467,0.7542905],"study_design_scores_gemma":[0.00002944899,0.0001396842,0.001761273,0.0002940788,0.00002897954,0.000211502,0.0003781597,0.75945,0.002454761,0.2036438,0.03152132,0.00008693295],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01698714,0.05252715,0.8697408,0.04761344,0.00121418,0.0001765725,0.0005825922,0.001350621,0.009807429],"genre_scores_gemma":[0.343971,0.03659111,0.5989221,0.004416633,0.004712093,0.0005261882,0.001227521,0.0003047266,0.0093286],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01176599,"threshold_uncertainty_score":0.06222522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005721709867167127,"score_gpt":0.2116527367988999,"score_spread":0.2059310269317327,"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."}}