{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001057243,0.0004242336,0.0002274052,0.0006158089,0.0001315879,0.0003712412,0.0003982683,0.0006118719,0.001229285],"category_scores_gemma":[0.001377754,0.0001997823,0.0001681624,0.0003434049,0.0003480505,0.0004117668,0.0003273364,0.0002669715,0.000406613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002634726,"about_ca_system_score_gemma":0.0004540416,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003700749,"about_ca_topic_score_gemma":0.0003057154,"domain_scores_codex":[0.9997097,0.00008251674,0.00002161318,0.0000412889,0.0001195239,0.00002536894],"domain_scores_gemma":[0.9994517,0.0002131998,0.00009813764,0.0000880521,0.0001057094,0.00004322059],"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":[0.0003234808,0.0001460496,0.001768725,0.0002430194,0.00002835272,0.0002972359,0.00005997528,0.003786053,0.9779738,0.0007538842,0.0002968472,0.01432257],"study_design_scores_gemma":[0.00006525798,0.002280192,0.008226406,0.00008461496,0.0001549838,0.003288327,0.00007638851,0.0418869,0.9345378,0.000405209,0.008946434,0.00004749856],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7552783,0.007916815,0.2292038,0.0003667201,0.0001405523,0.0004889472,0.0005510228,0.001055495,0.004998232],"genre_scores_gemma":[0.8691736,0.00197855,0.1250418,0.0001786145,0.00001559127,0.0004069036,0.0007225833,0.0001293851,0.002352918],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001229285,"threshold_uncertainty_score":0.005591273,"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."}}