{"id":"W4408837865","doi":"10.18502/fbt.v12i2.18283","title":"Implementation of the Wobbling Technique with Spatial Resolution Enhancement Approach in the Xtrim-PET Preclinical Scanner: Monte Carlo Simulation and Performance Evaluation","year":2025,"lang":"en","type":"article","venue":"Frontiers in biomedical technologies","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Monte Carlo method; Scanner; Resolution (logic); Image resolution; Medical physics; Computer science; Nuclear medicine; Artificial intelligence; Physics; Medicine; Mathematics; Statistics","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":[0.001524779,0.0001115636,0.0002262165,0.0003168256,0.00007508662,0.00001058792,0.0002462802,0.0001470571,0.000002338012],"category_scores_gemma":[0.0002884608,0.00006252501,0.00003010068,0.001020599,0.0006382825,0.00005722083,0.0001079125,0.0004152108,5.971494e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001572228,"about_ca_system_score_gemma":0.0001445826,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001225303,"about_ca_topic_score_gemma":0.00002105046,"domain_scores_codex":[0.9985067,0.000101099,0.0004570743,0.0002692309,0.0004865701,0.0001792881],"domain_scores_gemma":[0.9993148,0.0000789555,0.0001370803,0.000376582,0.00007593777,0.0000166795],"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":[0.0003511487,0.000665983,0.2813163,0.000407655,0.00004899579,0.000002011222,0.0003874378,0.0003678325,0.0009952014,0.0003774989,0.004061324,0.7110186],"study_design_scores_gemma":[0.003367633,0.000776338,0.154807,0.001339079,0.0001813852,0.0000141068,0.006285541,0.8165623,0.01085192,0.002044088,0.00357068,0.0001999814],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7265981,0.0004496176,0.2583827,0.01068541,0.00007589861,0.003562049,0.000004201464,0.0001217388,0.0001202781],"genre_scores_gemma":[0.935724,0.0002781167,0.06259921,0.00008421049,0.00001251449,0.001275176,0.00001389496,0.000004906977,0.000007922494],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8161944,"threshold_uncertainty_score":0.2549696,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03218671271555636,"score_gpt":0.3723442469441032,"score_spread":0.3401575342285469,"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."}}