{"id":"W1990656001","doi":"10.1118/1.4814188","title":"SU‐E‐I‐77: A Phantom to Assess EIT/CT Imaging System","year":2013,"lang":"en","type":"article","venue":"Medical Physics","topic":"Electrical and Bioimpedance Tomography","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Cancer Agency","funders":"","keywords":"Imaging phantom; Electrical impedance tomography; Scanner; Tomography; Materials science; Image quality; Biomedical engineering; Iterative reconstruction; Voltage; Electrode; Nuclear medicine; Medical imaging; Physics; Optics; Computer science; Artificial intelligence; Medicine; Image (mathematics)","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":[0.000114943,0.0001747717,0.0002331111,0.00004928165,0.00004796526,0.00006605993,0.0002788728,0.00003113236,0.0001121402],"category_scores_gemma":[0.00003120039,0.0001393381,0.00009680324,0.0005978454,0.00003715436,0.0001367339,0.000046792,0.0002726777,0.0006956334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005521067,"about_ca_system_score_gemma":0.00002187865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007221297,"about_ca_topic_score_gemma":0.00000199872,"domain_scores_codex":[0.9985775,0.00001969553,0.0002082422,0.0001950596,0.0005412463,0.000458235],"domain_scores_gemma":[0.9992464,0.00007344682,0.00001703113,0.0001970708,0.00004695711,0.0004191225],"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":[0.000007002615,0.0002469418,0.0141853,0.0008688932,0.0001782497,0.0002656199,0.0002146309,0.0002923514,0.01269233,0.002986969,0.09436282,0.8736989],"study_design_scores_gemma":[0.003712752,0.0003929846,0.02359008,0.002352259,0.0002495332,0.0003258356,0.0004456485,0.6963677,0.1896569,0.008846045,0.06954537,0.004514891],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7864301,0.000970608,0.1814353,0.001273182,0.001531876,0.0007633401,0.00001393104,0.002595872,0.02498577],"genre_scores_gemma":[0.9985764,0.00001273452,0.0001961657,0.0004267549,0.0006323539,0.000066783,0.000005418151,0.00003254514,0.00005081374],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.869184,"threshold_uncertainty_score":0.8941191,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009570856468774558,"score_gpt":0.2245134977442288,"score_spread":0.2149426412754543,"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."}}