{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005952175,0.0006652276,0.0009982393,0.0004172219,0.0001995877,0.001478137,0.0008323891,0.001691967,0.001532241],"category_scores_gemma":[0.01662117,0.0005543465,0.0005293821,0.0005176009,0.001056464,0.001593663,0.0004584621,0.001267551,0.0007694088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004095807,"about_ca_system_score_gemma":0.0005802012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009256274,"about_ca_topic_score_gemma":0.00221463,"domain_scores_codex":[0.9981548,0.0009401939,0.00009455458,0.0001583944,0.0005639345,0.00008805744],"domain_scores_gemma":[0.9932758,0.004022793,0.001109331,0.0004520731,0.0009114239,0.0002286172],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00355412,0.000456697,0.02933967,0.003179721,0.0006026852,0.0009933017,0.0005979332,0.008001295,0.2892532,0.003157742,0.008849489,0.6520141],"study_design_scores_gemma":[0.0006823632,0.01195846,0.1507169,0.0046719,0.002206419,0.01614975,0.001394458,0.08967337,0.5772299,0.01259185,0.131857,0.000867537],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4285938,0.2680315,0.2317907,0.058195,0.002748716,0.000244629,0.0003162082,0.0017624,0.008317021],"genre_scores_gemma":[0.7367549,0.05636725,0.1939109,0.007378745,0.001328567,0.0001525749,0.0003201849,0.0007347729,0.003052111],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005952175,"threshold_uncertainty_score":0.03147852,"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."}}