{"id":"W4414654640","doi":"10.2967/jnmt.125.269555","title":"Clinical Evaluation of BSREM Reconstruction in Pediatric Oncology Using [ <sup>18</sup> F]FDG PET/CT","year":2025,"lang":"en","type":"article","venue":"Journal of Nuclear Medicine Technology","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"","keywords":"Iterative reconstruction; Image quality; Pediatric oncology; Regularization (linguistics); Image resolution; Retrospective cohort study; Reconstruction algorithm","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":[0.002237111,0.0002794432,0.0002260737,0.0005213281,0.0001432153,0.0004384005,0.0003188882,0.0002882726,0.0008472177],"category_scores_gemma":[0.008859657,0.0002056393,0.0001866722,0.0004214863,0.0004421329,0.0003711988,0.0003518789,0.0001768244,0.0002428436],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002758108,"about_ca_system_score_gemma":0.0002383169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005754917,"about_ca_topic_score_gemma":0.0007143554,"domain_scores_codex":[0.9988831,0.0005432622,0.0001222107,0.0001660651,0.0002346901,0.00005070247],"domain_scores_gemma":[0.9972332,0.001329243,0.0006419187,0.0002148359,0.0004579369,0.0001228812],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002541583,0.0001320207,0.8604255,0.0001693526,0.0000992946,0.003087495,0.0005907456,0.009852067,0.04807319,0.0002005248,0.0003917764,0.07443652],"study_design_scores_gemma":[0.00008962689,0.003342249,0.8658404,0.00004900351,0.0002085801,0.02536747,0.0005302033,0.03834824,0.06361769,0.0001283081,0.002428591,0.00004961208],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9943308,0.0003766598,0.004533918,0.00002910214,0.00000254144,0.00002571296,0.00005980278,0.00003855046,0.0006030307],"genre_scores_gemma":[0.9920623,0.0003020477,0.007343505,0.00002086372,0.00000702909,0.0000173042,0.0001242271,0.00002722211,0.00009550181],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002237111,"threshold_uncertainty_score":0.0118311,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08664743076447338,"score_gpt":0.4569768195157283,"score_spread":0.3703293887512549,"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."}}