{"id":"W2133832313","doi":"10.1109/tns.2003.823025","title":"Phantom Studies Investigating Extravascular Density Imaging for Partial Volume Correction of 3-D PET&amp;lt;tex&amp;gt;$^18$&amp;lt;/tex&amp;gt;FDG Studies","year":2004,"lang":"en","type":"article","venue":"IEEE Transactions on Nuclear Science","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Imaging phantom; Partial volume; Nuclear medicine; Ventricle; Cardiac PET; Biomedical engineering; Artifact (error); Materials science; Scanner; Subtraction; Positron emission tomography; Physics; Cardiac imaging; Background subtraction; Image resolution; Mathematics; Medicine; Optics; Cardiology; Pixel; Computer science; Artificial intelligence","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":["metaepi_narrow","sts"],"consensus_categories":["sts"],"category_scores_codex":[0.001425523,0.0003777847,0.0006777719,0.0003822859,0.001418697,0.00008597174,0.0004081466,0.00008332215,0.000122916],"category_scores_gemma":[0.0007180723,0.0003473259,0.0003125914,0.001249385,0.002813133,0.0004431055,0.00002343649,0.0005112909,0.000106805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004201237,"about_ca_system_score_gemma":0.0002781635,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001392048,"about_ca_topic_score_gemma":0.0001868849,"domain_scores_codex":[0.9965494,0.00006963386,0.0007456731,0.0009212896,0.001033444,0.0006805732],"domain_scores_gemma":[0.9972518,0.0002243316,0.0002972945,0.0008957766,0.000931255,0.0003995234],"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":[0.0001878309,0.001323427,0.0002620621,0.0005600573,0.0004498082,0.00001081588,0.00858406,0.006567977,0.9253322,0.0003542614,0.01266433,0.04370313],"study_design_scores_gemma":[0.01681644,0.002664373,0.005105759,0.01310228,0.007436885,0.00266878,0.009821839,0.1305933,0.4541993,0.006211871,0.345471,0.005908152],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.643068,0.0003907619,0.3503503,0.003529876,0.00105061,0.0009749309,0.00002347495,0.0005009629,0.000111063],"genre_scores_gemma":[0.8787895,0.0004872118,0.1190803,0.0005919891,0.0001521707,0.0001421106,0.00000364702,0.00005529667,0.0006976821],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.471133,"threshold_uncertainty_score":0.9999006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08886180707879834,"score_gpt":0.371705813799771,"score_spread":0.2828440067209727,"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."}}