{"id":"W4406035971","doi":"10.3934/mbe.2025005","title":"Computational physics and imaging in medicine","year":2025,"lang":"en","type":"article","venue":"Mathematical Biosciences & Engineering","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto; University Health Network","funders":"","keywords":"Medical physics; Medical imaging; Medicine; Computer science; Radiology","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":[0.0003534922,0.00008691805,0.0002054924,0.0001464406,0.00003528086,0.0000208738,0.00006500904,0.00001887509,0.00002005998],"category_scores_gemma":[0.0005404828,0.00006526412,0.00001856391,0.0003697287,0.0001834056,0.00005540537,0.00004240371,0.0001667624,0.000002718166],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002669303,"about_ca_system_score_gemma":0.0000259737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006776237,"about_ca_topic_score_gemma":1.289617e-7,"domain_scores_codex":[0.9992677,0.000006875633,0.0001970016,0.0001708057,0.0001828932,0.0001747359],"domain_scores_gemma":[0.9996075,0.0002074521,0.00001760475,0.00007352257,0.00001756046,0.00007636235],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001710955,0.0002387222,0.08244991,0.001159577,0.00003344512,0.0001154581,0.00155352,0.01903968,0.02385086,0.7873837,0.0006560844,0.08350191],"study_design_scores_gemma":[0.0004567693,0.00001622304,0.01826039,0.000645409,0.00001491303,0.00003396504,0.0000780547,0.9606611,0.00009373558,0.01918113,0.0004890487,0.00006925003],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3225924,0.0005559635,0.654522,0.0149976,0.0001958519,0.0002026943,4.737485e-7,0.0001117882,0.006821218],"genre_scores_gemma":[0.9728361,0.000009949771,0.02648885,0.0005283748,0.000043991,0.000004849356,0.000001326942,0.000005433022,0.00008108201],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9416214,"threshold_uncertainty_score":0.2661394,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007463828576908736,"score_gpt":0.2896826965871456,"score_spread":0.2822188680102368,"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."}}