{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001835285,0.0007747791,0.0003832723,0.0004554461,0.0001852726,0.0006902154,0.0008078942,0.0005648664,0.002533909],"category_scores_gemma":[0.005606385,0.0006005584,0.0003379525,0.0005791084,0.0003883755,0.0004522156,0.0003722847,0.0004418938,0.0007276513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000438395,"about_ca_system_score_gemma":0.0003807454,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004309065,"about_ca_topic_score_gemma":0.0005726857,"domain_scores_codex":[0.9994172,0.0003194099,0.00002996139,0.00007771584,0.0001241819,0.0000316347],"domain_scores_gemma":[0.9967989,0.0021631,0.0003523721,0.0003558969,0.0002422686,0.00008747693],"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":[0.0005659602,0.0001356054,0.001670307,0.0004577532,0.00007503617,0.0004106341,0.0001679135,0.006698298,0.9563203,0.003195104,0.0009693482,0.02933376],"study_design_scores_gemma":[0.0001543753,0.002708797,0.007775391,0.0001267418,0.0002733975,0.006605064,0.00008178828,0.05539984,0.8876707,0.001405579,0.03770137,0.00009699177],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1643374,0.006668086,0.8198146,0.0003967085,0.0002550836,0.0007597479,0.000449446,0.001987551,0.005331428],"genre_scores_gemma":[0.3516637,0.002990697,0.6374425,0.000358593,0.0000611839,0.001105249,0.0009093147,0.001017157,0.004451659],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002533909,"threshold_uncertainty_score":0.00970602,"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."}}