{"id":"W3028921830","doi":"10.1245/s10434-020-08696-z","title":"A Novel Classification of Intrahepatic Cholangiocarcinoma Phenotypes Using Machine Learning Techniques: An International Multi-Institutional Analysis","year":2020,"lang":"en","type":"article","venue":"Annals of Surgical Oncology","topic":"Cholangiocarcinoma and Gallbladder Cancer Studies","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Medicine; Surgical oncology; Confidence interval; Intrahepatic Cholangiocarcinoma; Internal medicine; Gastroenterology; Cluster (spacecraft); Neutrophil to lymphocyte ratio; Overall survival","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":[0.0002457888,0.0001408439,0.0006510727,0.0002408304,0.00005331715,0.000005517734,0.0001372705,0.0001227615,0.0001020865],"category_scores_gemma":[0.0000969263,0.0001162935,0.0002842054,0.0005245305,0.0002193436,0.0001275612,0.00006877792,0.0002215079,0.000002041897],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005252756,"about_ca_system_score_gemma":0.0001525228,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003514134,"about_ca_topic_score_gemma":0.00005352021,"domain_scores_codex":[0.9987233,0.00007218072,0.0005015342,0.0002811718,0.0002637441,0.0001580571],"domain_scores_gemma":[0.9989396,0.0001002438,0.0002832333,0.00013314,0.0004021713,0.000141629],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001842715,0.001639822,0.8522173,0.000151317,0.002942765,0.0001259905,0.00177593,0.0004650116,0.1088843,0.001856165,0.00004500223,0.02805377],"study_design_scores_gemma":[0.003670706,0.002608941,0.7857932,0.00008415385,0.001608247,0.0001338313,0.0004353171,0.1398814,0.02044787,0.00002240649,0.04499044,0.0003234239],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9809496,0.0007227093,0.008277657,0.007524509,0.00007139784,0.0002290518,0.000059457,0.00005797308,0.002107654],"genre_scores_gemma":[0.9888947,0.0005844927,0.009732702,0.0004131857,0.0001851469,0.00001007591,0.0001555221,0.00001019596,0.00001395803],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1394164,"threshold_uncertainty_score":0.4742313,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1944087144866603,"score_gpt":0.4023918191472349,"score_spread":0.2079831046605746,"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."}}