{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00135417,0.00057948,0.001231033,0.001453448,0.0005336272,0.003686796,0.001066345,0.001806861,0.006230916],"category_scores_gemma":[0.006008418,0.0003996489,0.0005991357,0.001223965,0.003180306,0.002654455,0.002220348,0.002981436,0.001574667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001137681,"about_ca_system_score_gemma":0.001714655,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001407591,"about_ca_topic_score_gemma":0.0009310069,"domain_scores_codex":[0.9991726,0.0003260408,0.00004972322,0.000122432,0.0002894705,0.00003975093],"domain_scores_gemma":[0.9973553,0.001681341,0.0001947541,0.0003427632,0.000307859,0.0001180032],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001004566,0.00002124214,0.0004775269,0.0004144804,0.00003823862,0.0000475348,0.0001075871,0.007742898,0.0006029999,0.9082866,0.01418585,0.0680651],"study_design_scores_gemma":[0.000008165961,0.00001265846,0.0004355578,0.0001699056,0.00001930132,0.0001921931,0.00006881812,0.03800471,0.0005810922,0.8750833,0.08540829,0.00001614106],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009380935,0.1090427,0.7444195,0.04993043,0.005783148,0.0001034557,0.0005259162,0.0005853268,0.08022873],"genre_scores_gemma":[0.4095214,0.1124694,0.3867822,0.008892121,0.01216052,0.000605233,0.0008503451,0.0006399708,0.06807876],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006230916,"threshold_uncertainty_score":0.02084452,"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."}}