{"id":"W4392850630","doi":"10.1038/s42256-024-00807-9","title":"Foundation model for cancer imaging biomarkers","year":2024,"lang":"en","type":"article","venue":"Nature Machine Intelligence","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":171,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"National Cancer Institute; National Institutes of Health; Deutsche Forschungsgemeinschaft; European Commission","keywords":"Foundation (evidence); Medicine; Cancer; Medical physics; Oncology; Internal medicine; History; Archaeology","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":[0.0004367054,0.0001825929,0.0002029759,0.0002112838,0.00009865106,0.0001050672,0.0001449144,0.0001258717,0.0001593201],"category_scores_gemma":[0.0004584454,0.0001438737,0.0001578437,0.0002962434,0.00008673746,0.0001268907,0.00003652235,0.0009705693,0.0000229402],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001357042,"about_ca_system_score_gemma":0.000183862,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009222369,"about_ca_topic_score_gemma":0.00001393152,"domain_scores_codex":[0.9987597,0.00001520243,0.0002547711,0.0004225983,0.0002657491,0.000281977],"domain_scores_gemma":[0.9993331,0.0001802279,0.00003966397,0.0001980962,0.0001144651,0.0001344179],"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":[0.0001038482,0.00003500413,0.001767931,0.0004408193,0.0001395874,0.00003952796,0.0002832748,0.003230919,0.003767389,0.01079125,0.006586129,0.9728143],"study_design_scores_gemma":[0.0001211897,0.0000228128,0.0001268386,0.0003475671,0.0001130087,0.00007100685,0.0000173772,0.9449968,0.001534327,0.005383329,0.04711792,0.0001478595],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002754257,0.01822447,0.9512619,0.02352452,0.001466548,0.0004466918,0.00002142237,0.0002918938,0.002008256],"genre_scores_gemma":[0.9732422,0.0005538741,0.0205505,0.003148062,0.0005044164,0.0000711152,0.00009424946,0.00005783459,0.00177779],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9726664,"threshold_uncertainty_score":0.5867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01321673221640112,"score_gpt":0.3650903186786272,"score_spread":0.3518735864622261,"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."}}