{"id":"W4324149157","doi":"10.3390/cancers15061751","title":"Machine Learning of Multi-Modal Tumor Imaging Reveals Trajectories of Response to Precision Treatment","year":2023,"lang":"en","type":"article","venue":"Cancers","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University Health Centre","funders":"","keywords":"Sunitinib; Medicine; Artificial intelligence; Medical imaging; Computer science; Machine learning; Nuclear medicine; Radiology; Cancer; Internal medicine","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":[0.0006872535,0.0001348294,0.0004127171,0.0002676515,0.00005680915,0.000006181416,0.00008352728,0.00002410217,0.000049977],"category_scores_gemma":[0.001595366,0.0001091965,0.0001085995,0.0004661645,0.00009272252,0.00003465457,0.00003729417,0.0001723377,0.00000915805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005323726,"about_ca_system_score_gemma":0.0003254727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000813795,"about_ca_topic_score_gemma":0.000006489201,"domain_scores_codex":[0.9988108,0.0001170265,0.0003323213,0.0002367904,0.0002627872,0.000240289],"domain_scores_gemma":[0.9991003,0.0003076771,0.0001303971,0.000208754,0.00008224428,0.000170678],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004698135,0.00007222699,0.2649166,0.0002826644,0.0001553688,0.0002074847,0.006971316,0.03161738,0.5756208,0.00004364779,0.001144134,0.1142702],"study_design_scores_gemma":[0.01127354,0.003009878,0.3780903,0.002140217,0.0003329027,0.0001074875,0.002654532,0.4892409,0.06416223,0.00007743265,0.04835335,0.0005572471],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962313,0.0005829833,0.001243989,0.001086506,0.0002445072,0.0003118093,0.00001788695,0.00008549658,0.0001955037],"genre_scores_gemma":[0.9944734,0.0001133341,0.003258631,0.0001373389,0.00007154061,0.00002415271,0.00001655116,0.00003260252,0.001872442],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5114586,"threshold_uncertainty_score":0.4452904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01923867940617929,"score_gpt":0.3311693829214438,"score_spread":0.3119307035152645,"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."}}