{"id":"W2345102747","doi":"10.1109/jmmct.2016.2560625","title":"Composite Tissue-Type and Probability Image for Ultrasound and Microwave Tomography","year":2016,"lang":"en","type":"article","venue":"IEEE journal on multiscale and multiphysics computational techniques","topic":"Microwave Imaging and Scattering Analysis","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Tomography; Property (philosophy); Ultrasound; Computer science; Computed tomography; Computer vision; Artificial intelligence; Image (mathematics); Iterative reconstruction; Medical physics; Radiology; 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":[0.0001852294,0.0002007064,0.0002418041,0.0001310954,0.0001719105,0.0001358364,0.0000629956,0.00005833845,0.000001282416],"category_scores_gemma":[0.00002275603,0.0001529087,0.0000565664,0.00009363129,0.0001719682,0.000193008,0.00001541096,0.0001437953,0.000001062046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003006324,"about_ca_system_score_gemma":0.000008120439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004322333,"about_ca_topic_score_gemma":0.00000166102,"domain_scores_codex":[0.999177,0.00003411365,0.0002542197,0.0002290926,0.0001168951,0.0001886257],"domain_scores_gemma":[0.9991364,0.0004003329,0.00006750757,0.00008906177,0.000183934,0.0001227865],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003347573,0.00004515664,0.002359041,0.0000797499,0.00009066595,0.000003269631,0.0001384709,0.0002740955,0.8733434,0.00007627245,0.0007382231,0.1228181],"study_design_scores_gemma":[0.002432064,0.0006061243,0.03031622,0.000751652,0.0001966158,0.0006012815,0.00003720317,0.03744835,0.8674728,0.05507955,0.003864696,0.001193443],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6491245,0.0002034625,0.3500281,0.0001782253,0.00007079726,0.0001803807,0.00004435451,0.000136175,0.00003397875],"genre_scores_gemma":[0.8475401,0.000340041,0.1518661,0.00006465024,0.0001244675,0.00001099662,0.00000732924,0.00002534721,0.00002102242],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1984156,"threshold_uncertainty_score":0.6235437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01043625919379752,"score_gpt":0.2514290194377207,"score_spread":0.2409927602439232,"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."}}