{"id":"W3093300333","doi":"10.1200/cci.20.00074","title":"Tailoring Therapy for Children With Neuroblastoma on the Basis of Risk Group Classification: Past, Present, and Future","year":2020,"lang":"en","type":"review","venue":"JCO Clinical Cancer Informatics","topic":"Neuroblastoma Research and Treatments","field":"Medicine","cited_by":72,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"National Cancer Institute; St. Baldrick's Foundation","keywords":"Neuroblastoma; Risk stratification; Artificial intelligence; Harmonization; Medicine; Machine learning; Oncology; Internal medicine; Computer science; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001575775,0.0004487633,0.001023647,0.001829869,0.0002030098,0.0008604771,0.0007764672,0.0009471082,0.001591606],"category_scores_gemma":[0.003814686,0.0001534092,0.0007850103,0.001906477,0.000371152,0.001241093,0.0005464853,0.001469456,0.0007584763],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009642232,"about_ca_system_score_gemma":0.002021096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00284616,"about_ca_topic_score_gemma":0.006022791,"domain_scores_codex":[0.9996201,0.0001284986,0.00007631807,0.00005528697,0.00009340177,0.00002637628],"domain_scores_gemma":[0.9985879,0.0008794309,0.0001627249,0.000029384,0.0002943231,0.00004628998],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004629494,0.000020003,0.0004448408,0.01090619,0.000102797,0.00003873761,0.00004809392,0.0002411913,0.0001989539,0.002924934,0.01757561,0.9674523],"study_design_scores_gemma":[0.00004775549,0.0001181476,0.00309549,0.03025145,0.0005534082,0.0010142,0.0001807144,0.0002983014,0.0003429583,0.004756594,0.9593042,0.00003681808],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0000839271,0.9984992,0.0001210104,0.0007196797,0.0001362386,0.000005003682,0.00002166518,0.00000502638,0.0004084021],"genre_scores_gemma":[0.0007906754,0.9980235,0.0003907889,0.000466361,0.0001260403,0.000008798722,0.00004643918,0.000001768618,0.0001455831],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.00284616,"threshold_uncertainty_score":0.008333564,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1376447301290392,"score_gpt":0.4222457445968021,"score_spread":0.2846010144677629,"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."}}