{"id":"W4388837377","doi":"10.2196/46474","title":"Noninvasive Staging of Lymph Node Status in Breast Cancer Using Machine Learning: External Validation and Further Model Development","year":2023,"lang":"en","type":"article","venue":"JMIR Cancer","topic":"Breast Cancer Treatment Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Breast cancer; Lymphovascular invasion; Nomogram; Cohort; Sentinel lymph node; Lymph node; Radiology; Sentinel node; Oncology; Internal medicine; Cancer; Metastasis","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.03280579,0.00158965,0.001244028,0.001206472,0.000491467,0.001449467,0.001690881,0.0008218865,0.001279602],"category_scores_gemma":[0.03236552,0.0004873243,0.001865097,0.0008306005,0.0007030784,0.001013717,0.001838122,0.002237967,0.0005043975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000971348,"about_ca_system_score_gemma":0.001780163,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006014062,"about_ca_topic_score_gemma":0.005086676,"domain_scores_codex":[0.9925089,0.005701907,0.0003467108,0.0007542717,0.0004741189,0.0002141773],"domain_scores_gemma":[0.9700342,0.02459494,0.00097116,0.002057876,0.002056383,0.0002854925],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001144798,0.001049198,0.2151637,0.0005248204,0.002045982,0.0003082977,0.0003405309,0.5921153,0.001636375,0.001426337,0.003854241,0.1803904],"study_design_scores_gemma":[0.00005379249,0.0002582958,0.01001326,0.00008920806,0.0001274934,0.00003559392,0.00004635509,0.9866452,0.0008161567,0.001437371,0.0004590146,0.00001840189],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6744437,0.00215821,0.316766,0.001002003,0.0001494385,0.0009901022,0.001610066,0.0009847066,0.001895859],"genre_scores_gemma":[0.9318906,0.0003221957,0.06322158,0.0001726355,0.00005428685,0.0007177519,0.002835256,0.00006727984,0.0007184737],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03280579,"threshold_uncertainty_score":0.1734957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02159235071639449,"score_gpt":0.3032036995650734,"score_spread":0.2816113488486789,"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."}}