{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007905512,0.0004108895,0.0002837949,0.000206223,0.0001350374,0.0003338098,0.0006342394,0.0004792682,0.0008220064],"category_scores_gemma":[0.001286624,0.000205417,0.0002147139,0.0001903086,0.000234888,0.0002692239,0.0002443064,0.0002688343,0.0001481063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000462507,"about_ca_system_score_gemma":0.000582722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001996338,"about_ca_topic_score_gemma":0.002311524,"domain_scores_codex":[0.9998287,0.00005324552,0.000008438004,0.00001962056,0.00007043761,0.00001948863],"domain_scores_gemma":[0.999491,0.0002726439,0.00007372581,0.00005699507,0.00008583147,0.00001987481],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003614158,0.0001603571,0.004112201,0.000254738,0.00005104122,0.0002932719,0.000113474,0.8961194,0.0546346,0.002239162,0.0002856783,0.04137463],"study_design_scores_gemma":[0.00001541782,0.0001934137,0.0005060268,0.000008417666,0.00001449402,0.00008932586,0.000008320962,0.976698,0.02178754,0.0001284352,0.0005401073,0.00001060535],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5692949,0.0009617465,0.4234748,0.0001870755,0.00002916171,0.0002276118,0.0001447875,0.001207212,0.004472684],"genre_scores_gemma":[0.8571779,0.0002835132,0.1414785,0.00003470499,0.000003415207,0.00007993387,0.00007420986,0.00007403272,0.0007937391],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001996338,"threshold_uncertainty_score":0.004180908,"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."}}