{"id":"W1965891716","doi":"10.1118/1.4870985","title":"Isotope specific resolution recovery image reconstruction in high resolution PET imaging","year":2014,"lang":"en","type":"article","venue":"Medical Physics","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; St. Thomas Hospital; Montreal Neurological Institute and Hospital","funders":"Engineering and Physical Sciences Research Council; Cancer Research UK","keywords":"Image resolution; Iterative reconstruction; Positron emission tomography; Imaging phantom; Point spread function; Resolution (logic); Positron; Computer science; Nuclear medicine; Range (aeronautics); Medical physics; Physics; Optics; Artificial intelligence; Materials science; Medicine; Nuclear physics","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":[],"consensus_categories":[],"category_scores_codex":[0.000851704,0.0001635109,0.0003149857,0.00009944226,0.000094068,0.00002546942,0.0001496304,0.00009084441,0.0003393294],"category_scores_gemma":[0.00053134,0.000151275,0.00009221896,0.000402195,0.0003184425,0.0001827124,0.00007216926,0.0006498752,0.0001263553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001916067,"about_ca_system_score_gemma":0.00009942483,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001411561,"about_ca_topic_score_gemma":0.000006140795,"domain_scores_codex":[0.9980624,0.00009698956,0.0004522316,0.0004129927,0.0006247666,0.0003506714],"domain_scores_gemma":[0.9989251,0.0001225698,0.0001113735,0.0004625916,0.00009384203,0.0002845352],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001856086,0.0007053154,0.005980768,0.0001740905,0.00002025513,0.0001034201,0.00007297784,0.00000861944,0.01589271,0.0167803,0.113233,0.8468429],"study_design_scores_gemma":[0.01132497,0.0007769373,0.05708252,0.004905376,0.0002381503,0.002085034,0.0001730119,0.3279058,0.02865919,0.3019578,0.2630538,0.001837462],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2116495,0.000116131,0.7331442,0.03948659,0.0006769022,0.0007699776,0.000011147,0.0005590725,0.0135865],"genre_scores_gemma":[0.9531958,0.0004357647,0.042393,0.001801029,0.001648677,0.00009215746,0.0001589702,0.00004129185,0.0002333746],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8450055,"threshold_uncertainty_score":0.6168815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01440955093841598,"score_gpt":0.2730019267470768,"score_spread":0.2585923758086608,"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."}}