{"id":"W3033635662","doi":"10.18383/j.tom.2019.00027","title":"4D-CT Attenuation Correction in Respiratory-Gated PET for Hypoxia Imaging: Is It Really Beneficial?","year":2020,"lang":"en","type":"article","venue":"Tomography","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University Health Network; University of Toronto; Ontario Institute for Cancer Research","funders":"Ontario Institute for Cancer Research","keywords":"Nuclear medicine; Positron emission tomography; Correction for attenuation; Imaging phantom; Attenuation; Positron emission; Hypoxia (environmental); Pet imaging; Reproducibility; Medicine; Biomedical engineering; Physics; Chemistry; Oxygen; Optics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002336312,0.0001284707,0.000213239,0.0002046932,0.00008148729,0.00002742352,0.000096006,0.00003089371,0.0001116906],"category_scores_gemma":[0.0001713807,0.0001246914,0.0001291746,0.0008271586,0.00007370933,0.00006460383,0.00002072846,0.000199486,0.00001422184],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000288301,"about_ca_system_score_gemma":0.0000681286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009823457,"about_ca_topic_score_gemma":0.00001465965,"domain_scores_codex":[0.9988972,0.00002272213,0.0003288922,0.000331037,0.0002140218,0.0002061074],"domain_scores_gemma":[0.9993175,0.000059872,0.0000951943,0.0002226508,0.0001317412,0.0001730419],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002630591,0.0003484068,0.06767236,0.0001902818,0.00005013558,0.00004885175,0.000709093,0.000007598262,0.03785527,0.001366859,0.847717,0.04377107],"study_design_scores_gemma":[0.003723937,0.000715219,0.05002804,0.0004137315,0.0002779325,0.00005362946,0.0004413408,0.09244339,0.02713671,0.001644188,0.822519,0.0006028552],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6610147,0.000329287,0.08442234,0.2422786,0.0004170597,0.003935589,0.0001099018,0.001252066,0.00624049],"genre_scores_gemma":[0.9716309,0.00002780423,0.006648861,0.02105363,0.0002252426,0.0001915211,0.000120308,0.00003031455,0.00007140472],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3106163,"threshold_uncertainty_score":0.5084769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04032803920171399,"score_gpt":0.3237012284162972,"score_spread":0.2833731892145832,"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."}}