{"id":"W3014785343","doi":"10.1148/rycan.2020190079","title":"Decoding and Systematization of Medical Imaging Features of Multiple Human Malignancies","year":2020,"lang":"en","type":"article","venue":"Radiology Imaging Cancer","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"China Scholarship Council; China Postdoctoral Science Foundation","keywords":"Malignancy; Feature (linguistics); Medical imaging; Cluster analysis; Medicine; Feature selection; Computer science; Pattern recognition (psychology); Artificial intelligence; Pathology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01650133,0.001142228,0.001997031,0.02377807,0.0005383336,0.003088933,0.001177192,0.0007208981,0.002551501],"category_scores_gemma":[0.07746615,0.000502376,0.004690049,0.01276649,0.0008874849,0.002381461,0.00163638,0.0006747205,0.0005213873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001379125,"about_ca_system_score_gemma":0.002936454,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002215617,"about_ca_topic_score_gemma":0.002805284,"domain_scores_codex":[0.9854087,0.005440685,0.004410526,0.002272835,0.002224249,0.0002429501],"domain_scores_gemma":[0.9281394,0.05095933,0.009981888,0.004812006,0.005849455,0.0002578133],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001391532,0.0001065181,0.1489479,0.09440271,0.01614955,0.001232033,0.001882261,0.007072068,0.01259856,0.008045996,0.009746167,0.6984246],"study_design_scores_gemma":[0.0006643158,0.002103729,0.4626023,0.0506464,0.1064265,0.009738874,0.004389313,0.04390065,0.04035985,0.07052868,0.207836,0.00080358],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2351548,0.2954445,0.3657923,0.004703948,0.0008984251,0.003583401,0.07593335,0.002195787,0.01629342],"genre_scores_gemma":[0.7705555,0.03374928,0.1645882,0.0007561868,0.000472044,0.002305333,0.02666942,0.0001740007,0.0007299198],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02377807,"threshold_uncertainty_score":0.08726835,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01360978325406095,"score_gpt":0.3196896325571045,"score_spread":0.3060798493030435,"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."}}